som
Paleta de colores para la visualización de la malla tipo mapa de calor ( Shane Lynn 14-01-2014 )
coolBlueHotRed <- function(n, alpha = 1) {
rainbow(n, end=4/6, alpha=alpha)[n:1]
} cargamos los datos de discricoches
library(haven)
discricoches <- read_sav("discricochesR10.sav")
names(discricoches)## [1] "sexo" "edad" "grupedad" "naños"
## [5] "tipovehiculo" "antigvehiculo" "edadvehiculo" "antigcarnet"
## [9] "kilometros" "siniUA"instalamos y cargamos el paquete kohonen
library(kohonen)Generamos el conjunto de entenamiento y lo conviertimos en matriz Prescindimos de la variable sinUA porque de alguna manera nos interesará quizá confrontar los grupos obtenidos con el comportamiento de esta variable. Tipificamos las variables antes de proceder al entrenamiento para que todas tengan el mismo peso
data_train <- discricoches[, c(1,2,3,4,5,6,7,8,9)]
data_train_matrix <- as.matrix(scale(data_train))
summary(data_train)## sexo edad grupedad naños
## Min. :0.0000 Min. :18.00 Min. :1.000 Min. : 1.000
## 1st Qu.:0.0000 1st Qu.:24.00 1st Qu.:1.000 1st Qu.: 4.000
## Median :0.0000 Median :30.00 Median :2.000 Median : 6.000
## Mean :0.4815 Mean :32.15 Mean :1.895 Mean : 7.857
## 3rd Qu.:1.0000 3rd Qu.:37.00 3rd Qu.:2.000 3rd Qu.:12.000
## Max. :1.0000 Max. :60.00 Max. :4.000 Max. :18.000
## tipovehiculo antigvehiculo edadvehiculo antigcarnet
## Min. :1.000 Min. :1.000 Min. : 0.005877 Min. : 0.00
## 1st Qu.:2.000 1st Qu.:1.000 1st Qu.: 0.749155 1st Qu.: 5.00
## Median :2.000 Median :2.000 Median : 2.018385 Median :12.00
## Mean :2.236 Mean :1.979 Mean : 3.220343 Mean :13.44
## 3rd Qu.:3.000 3rd Qu.:2.000 3rd Qu.: 3.681040 3rd Qu.:19.00
## Max. :4.000 Max. :4.000 Max. :15.000000 Max. :42.00
## kilometros
## Min. : 1380
## 1st Qu.: 16968
## Median : 34229
## Mean : 53329
## 3rd Qu.: 60094
## Max. :227700summary(data_train_matrix)## sexo edad grupedad naños
## Min. :-0.963 Min. :-1.4688 Min. :-1.1950 Min. :-1.3879
## 1st Qu.:-0.963 1st Qu.:-0.8461 1st Qu.:-1.1950 1st Qu.:-0.7806
## Median :-0.963 Median :-0.2235 Median : 0.1404 Median :-0.3758
## Mean : 0.000 Mean : 0.0000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 1.037 3rd Qu.: 0.5030 3rd Qu.: 0.1404 3rd Qu.: 0.8387
## Max. : 1.037 Max. : 2.8898 Max. : 2.8111 Max. : 2.0532
## tipovehiculo antigvehiculo edadvehiculo antigcarnet
## Min. :-1.5165 Min. :-1.13939 Min. :-0.9037 Min. :-1.3866
## 1st Qu.:-0.2893 1st Qu.:-1.13939 1st Qu.:-0.6948 1st Qu.:-0.8708
## Median :-0.2893 Median : 0.02481 Median :-0.3379 Median :-0.1486
## Mean : 0.0000 Mean : 0.00000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.9378 3rd Qu.: 0.02481 3rd Qu.: 0.1295 3rd Qu.: 0.5736
## Max. : 2.1649 Max. : 2.35321 Max. : 3.3118 Max. : 2.9464
## kilometros
## Min. :-0.9699
## 1st Qu.:-0.6789
## Median :-0.3566
## Mean : 0.0000
## 3rd Qu.: 0.1263
## Max. : 3.2556#grid (malla) creamos la malla. Especificamos el número de filas y columnas y la topología d ela malla (hexagonal o circular) 8 x 8 ( es cuadrada y 64 en relación a 704 es una buena reducción)
som_grid <- somgrid(xdim = 8, ydim=8, topo="hexagonal")
#summary(som_grid)Entrenamiento de la red
fijamos la semilla aleatoria <<set.seed(24)>> ,por ejemplo creamos el modelo/entrenamos la red , fijando el número de iteraciones(600) las ratios de aprendizaje(inicial y final), (también puede especificarse el radio de vecindad)
set.seed(24)
som_model <- som(data_train_matrix,
grid=som_grid,
rlen=600,
alpha=c(0.05,0.01),
keep.data = TRUE )
summary(som_model)## SOM of size 8x8 with a hexagonal topology and a bubble neighbourhood function.
## The number of data layers is 1.
## Distance measure(s) used: sumofsquares.
## Training data included: 704 objects.
## Mean distance to the closest unit in the map: 0.398.Entre los 13 atributos del objeto som creado (tenemos ) que incluyen los parámetros del aprendizaje y otras características tenemos también:
som_model$unit.classif nos indicada el nodo al que ha sido asuignada cada instancia los nodos están numerados desde el extremo inferior izquierdo hasta el extremo superior derecho
som_model$unit.classif ## [1] 41 57 57 57 57 57 41 57 57 57 49 49 49 49 49 50 50 34 57 58 58 58 58 58 9
## [26] 41 35 50 50 50 50 50 50 9 41 41 41 33 33 41 33 33 33 33 33 33 33 33 33 33
## [51] 33 33 33 33 33 41 41 33 41 41 41 33 41 10 58 43 19 19 18 19 51 51 3 18 3
## [76] 54 8 8 49 51 51 49 50 58 43 58 49 50 58 43 58 50 50 50 50 58 9 33 9 9
## [101] 10 10 33 9 9 9 57 27 17 25 17 17 17 58 34 41 34 27 27 17 58 34 58 41 57
## [126] 25 17 17 17 58 41 34 34 41 57 27 27 27 17 17 17 57 57 33 27 27 25 58 58 34
## [151] 25 17 17 17 34 41 34 41 34 57 58 33 27 25 17 17 58 34 58 27 25 27 34 41 33
## [176] 25 17 58 41 41 57 27 25 25 27 25 27 25 62 60 62 62 60 44 60 36 36 60 62 60
## [201] 36 62 62 60 44 36 62 36 60 62 44 60 36 36 60 60 36 36 62 60 62 44 44 62 60
## [226] 62 60 60 60 62 60 60 62 60 44 36 62 36 62 44 62 44 60 44 36 60 62 44 62 62
## [251] 60 36 62 62 62 44 62 44 60 60 60 36 44 36 60 36 44 62 36 62 60 62 36 36 62
## [276] 60 62 60 60 44 44 60 62 62 62 62 60 44 60 36 60 60 62 36 62 60 1 9 1 1
## [301] 1 9 1 1 1 1 1 9 1 1 9 1 9 1 9 30 64 30 30 30 24 30 64 53 53
## [326] 64 64 53 19 11 19 11 11 19 19 32 32 39 32 39 39 39 24 37 53 53 47 37 3 2
## [351] 32 32 32 32 39 39 63 24 47 23 53 47 37 23 2 2 32 30 32 39 32 32 32 37 23
## [376] 47 37 53 12 32 39 30 32 32 39 32 32 37 53 37 37 23 12 3 2 2 30 37 24 37
## [401] 47 53 47 23 37 23 32 39 32 32 37 37 53 32 32 32 32 39 32 32 24 47 23 2 39
## [426] 37 53 23 3 32 32 24 37 23 23 32 24 53 53 47 23 2 32 37 37 53 23 3 12 30
## [451] 30 47 15 46 30 6 47 46 30 30 15 46 30 47 15 46 30 6 47 16 16 16 16 16 16
## [476] 16 16 42 50 42 42 50 50 10 19 10 32 54 54 54 62 63 62 54 63 54 63 54 63 28
## [501] 62 28 51 51 28 51 51 51 51 56 48 64 48 64 48 48 56 64 48 64 64 64 3 56 48
## [526] 64 64 64 64 56 64 48 64 64 64 48 20 32 3 53 53 21 21 30 40 40 21 30 40 40
## [551] 21 30 40 21 23 40 21 21 39 15 21 21 21 21 15 14 5 14 5 14 6 6 13 13 13
## [576] 13 6 6 4 6 8 8 8 8 8 8 8 8 8 8 8 8 8 8 42 58 58 42 58 58
## [601] 42 42 42 42 58 42 43 36 19 64 48 64 64 64 56 64 56 12 64 64 3 56 56 56 56
## [626] 2 56 20 40 48 40 30 40 21 23 23 20 30 40 21 5 15 21 15 14 4 4 4 4 13
## [651] 5 5 5 46 5 6 5 6 6 6 13 6 13 7 7 7 4 8 8 8 8 8 8 8 48
## [676] 56 8 40 64 64 64 8 8 64 40 52 21 5 14 52 44 64 18 18 12 3 64 56 8 16
## [701] 15 64 14 42#som_model$data sson los datos originales
som_model$data## [[1]]
## sexo edad grupedad naños tipovehiculo antigvehiculo
## [1,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [2,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [3,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [4,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [5,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [6,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [7,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [8,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [9,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [10,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [11,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 -1.13939500
## [12,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 -1.13939500
## [13,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 -1.13939500
## [14,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 -1.13939500
## [15,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 -1.13939500
## [16,] -0.9630409 -1.26122987 -1.1950205 -1.38784996 -0.2893481 -1.13939500
## [17,] -0.9630409 -1.26122987 -1.1950205 -1.38784996 -0.2893481 -1.13939500
## [18,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [19,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [20,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [21,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [22,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [23,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [24,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [25,] 1.0369025 -1.05367825 -1.1950205 -0.98302445 0.9377669 2.35320621
## [26,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [27,] 1.0369025 -0.43102339 0.1403675 -1.18543720 0.9377669 0.02480541
## [28,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -0.2893481 -1.13939500
## [29,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -0.2893481 -1.13939500
## [30,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -0.2893481 -1.13939500
## [31,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -0.2893481 -1.13939500
## [32,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -0.2893481 -1.13939500
## [33,] -0.9630409 -1.46878150 -1.1950205 -1.38784996 -0.2893481 -1.13939500
## [34,] 1.0369025 -1.05367825 -1.1950205 -0.98302445 0.9377669 2.35320621
## [35,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [36,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [37,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [38,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [39,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [40,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [41,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [42,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [43,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [44,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [45,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [46,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [47,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [48,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [49,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [50,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [51,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [52,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [53,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [54,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [55,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [56,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [57,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [58,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [59,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [60,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [61,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [62,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -0.2893481 0.02480541
## [63,] 1.0369025 -1.46878150 -1.1950205 -1.38784996 -1.5164632 0.02480541
## [64,] -0.9630409 -1.05367825 0.1403675 -1.18543720 0.9377669 2.35320621
## [65,] -0.9630409 -0.84612663 -1.1950205 -0.37578618 -0.2893481 0.02480541
## [66,] -0.9630409 -0.84612663 -1.1950205 0.23145209 0.9377669 -1.13939500
## [67,] -0.9630409 -0.53479920 0.1403675 -0.57819894 -0.2893481 1.18900581
## [68,] -0.9630409 -0.53479920 0.1403675 -0.57819894 -0.2893481 1.18900581
## [69,] 1.0369025 -0.53479920 0.1403675 -0.57819894 -0.2893481 1.18900581
## [70,] -0.9630409 -0.22347177 0.1403675 -0.78061169 -1.5164632 1.18900581
## [71,] -0.9630409 -0.22347177 0.1403675 -0.98302445 -1.5164632 -1.13939500
## [72,] -0.9630409 -0.22347177 0.1403675 -0.98302445 -0.2893481 -1.13939500
## [73,] 1.0369025 -0.22347177 0.1403675 0.02903933 0.9377669 2.35320621
## [74,] 1.0369025 -0.22347177 0.1403675 -0.37578618 -0.2893481 1.18900581
## [75,] 1.0369025 0.08785566 0.1403675 0.83869035 0.9377669 2.35320621
## [76,] 1.0369025 0.19163147 0.1403675 -0.37578618 -1.5164632 0.02480541
## [77,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [78,] -0.9630409 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [79,] -0.9630409 -0.74235082 -1.1950205 -1.18543720 -1.5164632 -1.13939500
## [80,] -0.9630409 -0.43102339 0.1403675 -1.18543720 -0.2893481 -1.13939500
## [81,] -0.9630409 -0.22347177 0.1403675 -0.98302445 -0.2893481 -1.13939500
## [82,] -0.9630409 -0.74235082 -1.1950205 -1.18543720 -1.5164632 -1.13939500
## [83,] -0.9630409 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [84,] -0.9630409 -0.84612663 -1.1950205 -0.37578618 -0.2893481 0.02480541
## [85,] -0.9630409 -0.84612663 -1.1950205 0.23145209 0.9377669 -1.13939500
## [86,] -0.9630409 -0.84612663 -1.1950205 -0.37578618 -0.2893481 0.02480541
## [87,] -0.9630409 -0.74235082 -1.1950205 -1.18543720 -1.5164632 -1.13939500
## [88,] -0.9630409 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [89,] -0.9630409 -0.84612663 -1.1950205 -0.37578618 -0.2893481 0.02480541
## [90,] -0.9630409 -0.84612663 -1.1950205 0.23145209 0.9377669 -1.13939500
## [91,] -0.9630409 -0.84612663 -1.1950205 -0.37578618 -0.2893481 0.02480541
## [92,] -0.9630409 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [93,] -0.9630409 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [94,] -0.9630409 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [95,] -0.9630409 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [96,] -0.9630409 -0.84612663 -1.1950205 -0.37578618 -0.2893481 0.02480541
## [97,] 1.0369025 -1.36500569 -1.1950205 -1.38784996 0.9377669 2.35320621
## [98,] 1.0369025 -1.36500569 -1.1950205 -1.38784996 0.9377669 0.02480541
## [99,] 1.0369025 -1.36500569 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [100,] 1.0369025 -1.36500569 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [101,] -0.9630409 -1.36500569 -1.1950205 -1.38784996 0.9377669 2.35320621
## [102,] -0.9630409 -1.36500569 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [103,] 1.0369025 -1.36500569 -1.1950205 -1.38784996 0.9377669 0.02480541
## [104,] 1.0369025 -1.36500569 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [105,] 1.0369025 -1.36500569 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [106,] 1.0369025 -1.36500569 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [107,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [108,] -0.9630409 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [109,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [110,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [111,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [112,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [113,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [114,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [115,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [116,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [117,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [118,] -0.9630409 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [119,] -0.9630409 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [120,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [121,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [122,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [123,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [124,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [125,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [126,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [127,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [128,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [129,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [130,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [131,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [132,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [133,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [134,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [135,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [136,] -0.9630409 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [137,] -0.9630409 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [138,] -0.9630409 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [139,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [140,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [141,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [142,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [143,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [144,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [145,] -0.9630409 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [146,] -0.9630409 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [147,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [148,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [149,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [150,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [151,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [152,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [153,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [154,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [155,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [156,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [157,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [158,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [159,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [160,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [161,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [162,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [163,] -0.9630409 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [164,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [165,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [166,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [167,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [168,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [169,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [170,] -0.9630409 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [171,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [172,] -0.9630409 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [173,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [174,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [175,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [176,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [177,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [178,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -0.2893481 0.02480541
## [179,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [180,] 1.0369025 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [181,] -0.9630409 -0.94990244 -1.1950205 -0.98302445 -1.5164632 0.02480541
## [182,] -0.9630409 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [183,] 1.0369025 -0.94990244 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [184,] 1.0369025 -0.74235082 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [185,] -0.9630409 -0.74235082 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [186,] 1.0369025 -0.74235082 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [187,] -0.9630409 -0.74235082 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [188,] 1.0369025 -0.74235082 -1.1950205 -0.57819894 -0.2893481 1.18900581
## [189,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [190,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [191,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [192,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [193,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [194,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [195,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [196,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [197,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [198,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [199,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [200,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [201,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [202,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [203,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [204,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [205,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [206,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [207,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [208,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [209,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [210,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [211,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [212,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [213,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [214,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [215,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [216,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [217,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [218,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [219,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [220,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [221,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [222,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [223,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [224,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [225,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [226,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [227,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [228,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [229,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [230,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [231,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [232,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [233,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [234,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [235,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [236,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [237,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [238,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [239,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [240,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [241,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [242,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [243,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [244,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [245,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [246,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [247,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [248,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [249,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [250,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [251,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [252,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [253,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [254,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [255,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [256,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [257,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [258,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [259,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [260,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [261,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [262,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [263,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [264,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [265,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [266,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [267,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [268,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [269,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [270,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [271,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [272,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [273,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [274,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [275,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [276,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [277,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [278,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [279,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [280,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [281,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [282,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [283,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [284,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [285,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [286,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [287,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [288,] -0.9630409 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [289,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [290,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [291,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [292,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [293,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [294,] 1.0369025 -0.43102339 0.1403675 -0.37578618 2.1648819 0.02480541
## [295,] 1.0369025 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [296,] -0.9630409 -0.43102339 0.1403675 -0.37578618 -0.2893481 0.02480541
## [297,] -0.9630409 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [298,] 1.0369025 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [299,] -0.9630409 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [300,] -0.9630409 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [301,] -0.9630409 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [302,] 1.0369025 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [303,] -0.9630409 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [304,] -0.9630409 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [305,] -0.9630409 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [306,] -0.9630409 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [307,] -0.9630409 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [308,] 1.0369025 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [309,] -0.9630409 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [310,] -0.9630409 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [311,] 1.0369025 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [312,] -0.9630409 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [313,] 1.0369025 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [314,] -0.9630409 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [315,] 1.0369025 -0.22347177 -1.1950205 -1.38784996 -0.2893481 2.35320621
## [316,] 1.0369025 0.29540728 0.1403675 0.23145209 0.9377669 -1.13939500
## [317,] 1.0369025 0.29540728 0.1403675 1.64834137 -0.2893481 -1.13939500
## [318,] 1.0369025 0.29540728 0.1403675 0.23145209 0.9377669 -1.13939500
## [319,] 1.0369025 0.29540728 0.1403675 0.23145209 0.9377669 -1.13939500
## [320,] 1.0369025 0.29540728 0.1403675 0.23145209 0.9377669 -1.13939500
## [321,] -0.9630409 0.29540728 0.1403675 0.23145209 0.9377669 0.02480541
## [322,] 1.0369025 0.29540728 0.1403675 0.23145209 0.9377669 -1.13939500
## [323,] 1.0369025 0.29540728 0.1403675 1.64834137 -0.2893481 -1.13939500
## [324,] 1.0369025 0.29540728 0.1403675 0.23145209 -0.2893481 0.02480541
## [325,] 1.0369025 0.29540728 0.1403675 0.23145209 -0.2893481 0.02480541
## [326,] 1.0369025 0.29540728 0.1403675 1.64834137 -0.2893481 -1.13939500
## [327,] 1.0369025 0.29540728 0.1403675 1.64834137 -0.2893481 -1.13939500
## [328,] 1.0369025 0.29540728 0.1403675 0.23145209 -0.2893481 0.02480541
## [329,] -0.9630409 0.39918309 0.1403675 -0.57819894 -0.2893481 1.18900581
## [330,] 1.0369025 0.39918309 0.1403675 -0.57819894 -0.2893481 1.18900581
## [331,] -0.9630409 0.39918309 0.1403675 -0.57819894 -0.2893481 1.18900581
## [332,] 1.0369025 0.39918309 0.1403675 -0.57819894 -0.2893481 1.18900581
## [333,] 1.0369025 0.39918309 0.1403675 -0.57819894 -0.2893481 1.18900581
## [334,] -0.9630409 0.39918309 0.1403675 -0.57819894 -0.2893481 1.18900581
## [335,] -0.9630409 0.39918309 0.1403675 -0.57819894 -0.2893481 1.18900581
## [336,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [337,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [338,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 -1.13939500
## [339,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [340,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 -1.13939500
## [341,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 -1.13939500
## [342,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 -1.13939500
## [343,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [344,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [345,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [346,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [347,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [348,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [349,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [350,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [351,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [352,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [353,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [354,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [355,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 -1.13939500
## [356,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 -1.13939500
## [357,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 -1.13939500
## [358,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [359,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [360,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [361,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [362,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [363,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [364,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [365,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [366,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [367,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [368,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [369,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [370,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 -1.13939500
## [371,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [372,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [373,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [374,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [375,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [376,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [377,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [378,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [379,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [380,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [381,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 -1.13939500
## [382,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [383,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [384,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [385,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 -1.13939500
## [386,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [387,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [388,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [389,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [390,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [391,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [392,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [393,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [394,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [395,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [396,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [397,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [398,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [399,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [400,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [401,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [402,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [403,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [404,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [405,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [406,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [407,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [408,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 -1.13939500
## [409,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [410,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [411,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [412,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [413,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [414,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [415,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [416,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [417,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [418,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 -1.13939500
## [419,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [420,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [421,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [422,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [423,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [424,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [425,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 -1.13939500
## [426,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [427,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [428,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [429,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [430,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [431,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [432,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [433,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [434,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [435,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [436,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [437,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [438,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [439,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [440,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [441,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [442,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [443,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 -1.13939500
## [444,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [445,] 1.0369025 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [446,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 0.02480541
## [447,] -0.9630409 0.50295890 0.1403675 0.23145209 0.9377669 0.02480541
## [448,] 1.0369025 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [449,] -0.9630409 0.50295890 0.1403675 0.23145209 -0.2893481 2.35320621
## [450,] 1.0369025 1.12561376 1.4757555 0.23145209 0.9377669 -1.13939500
## [451,] 1.0369025 1.12561376 1.4757555 0.23145209 0.9377669 -1.13939500
## [452,] -0.9630409 1.12561376 1.4757555 -0.98302445 -1.5164632 0.02480541
## [453,] -0.9630409 1.12561376 1.4757555 0.23145209 0.9377669 0.02480541
## [454,] 1.0369025 1.12561376 1.4757555 -0.98302445 -0.2893481 0.02480541
## [455,] 1.0369025 1.12561376 1.4757555 0.23145209 0.9377669 -1.13939500
## [456,] -0.9630409 1.12561376 1.4757555 1.64834137 -1.5164632 -1.13939500
## [457,] -0.9630409 1.12561376 1.4757555 -0.98302445 -1.5164632 0.02480541
## [458,] 1.0369025 1.12561376 1.4757555 -0.98302445 -0.2893481 0.02480541
## [459,] 1.0369025 1.12561376 1.4757555 0.23145209 0.9377669 -1.13939500
## [460,] 1.0369025 1.12561376 1.4757555 0.23145209 0.9377669 -1.13939500
## [461,] -0.9630409 1.12561376 1.4757555 0.23145209 0.9377669 0.02480541
## [462,] 1.0369025 1.12561376 1.4757555 -0.98302445 -0.2893481 0.02480541
## [463,] 1.0369025 1.12561376 1.4757555 0.23145209 0.9377669 -1.13939500
## [464,] -0.9630409 1.12561376 1.4757555 -0.98302445 -1.5164632 0.02480541
## [465,] -0.9630409 1.12561376 1.4757555 0.23145209 0.9377669 0.02480541
## [466,] 1.0369025 1.12561376 1.4757555 -0.98302445 -0.2893481 0.02480541
## [467,] 1.0369025 1.12561376 1.4757555 0.23145209 0.9377669 -1.13939500
## [468,] -0.9630409 1.12561376 1.4757555 1.64834137 -1.5164632 -1.13939500
## [469,] -0.9630409 1.12561376 1.4757555 -0.98302445 -1.5164632 0.02480541
## [470,] -0.9630409 1.33316538 1.4757555 -0.37578618 2.1648819 0.02480541
## [471,] -0.9630409 1.33316538 1.4757555 -0.37578618 2.1648819 0.02480541
## [472,] -0.9630409 1.33316538 1.4757555 -0.37578618 2.1648819 0.02480541
## [473,] -0.9630409 1.33316538 1.4757555 -0.37578618 2.1648819 0.02480541
## [474,] -0.9630409 1.33316538 1.4757555 -0.37578618 2.1648819 0.02480541
## [475,] -0.9630409 1.33316538 1.4757555 -0.37578618 2.1648819 0.02480541
## [476,] -0.9630409 1.33316538 1.4757555 -0.37578618 2.1648819 0.02480541
## [477,] -0.9630409 1.33316538 1.4757555 -0.37578618 2.1648819 0.02480541
## [478,] 1.0369025 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [479,] -0.9630409 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [480,] 1.0369025 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [481,] 1.0369025 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [482,] -0.9630409 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [483,] -0.9630409 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [484,] -0.9630409 -0.53479920 0.1403675 -0.78061169 -0.2893481 2.35320621
## [485,] -0.9630409 -0.53479920 0.1403675 -0.57819894 -0.2893481 1.18900581
## [486,] -0.9630409 -0.53479920 0.1403675 -0.78061169 -0.2893481 2.35320621
## [487,] -0.9630409 -0.43102339 0.1403675 0.02903933 0.9377669 -1.13939500
## [488,] 1.0369025 -0.32724758 0.1403675 -0.17337343 -1.5164632 0.02480541
## [489,] 1.0369025 -0.32724758 0.1403675 -0.17337343 -1.5164632 0.02480541
## [490,] 1.0369025 -0.32724758 0.1403675 -0.17337343 -1.5164632 0.02480541
## [491,] 1.0369025 -0.32724758 0.1403675 -0.17337343 -0.2893481 0.02480541
## [492,] 1.0369025 -0.32724758 0.1403675 -0.37578618 -0.2893481 -1.13939500
## [493,] 1.0369025 -0.32724758 0.1403675 -0.17337343 -0.2893481 0.02480541
## [494,] 1.0369025 -0.32724758 0.1403675 -0.17337343 -1.5164632 0.02480541
## [495,] 1.0369025 -0.32724758 0.1403675 -0.17337343 -0.2893481 -1.13939500
## [496,] 1.0369025 -0.32724758 0.1403675 -0.17337343 -1.5164632 0.02480541
## [497,] 1.0369025 -0.32724758 0.1403675 -0.37578618 -0.2893481 -1.13939500
## [498,] 1.0369025 -0.32724758 0.1403675 -0.17337343 -1.5164632 0.02480541
## [499,] 1.0369025 -0.32724758 0.1403675 -0.17337343 -0.2893481 -1.13939500
## [500,] 1.0369025 -0.22347177 0.1403675 0.02903933 0.9377669 1.18900581
## [501,] 1.0369025 -0.22347177 0.1403675 -0.78061169 -0.2893481 0.02480541
## [502,] 1.0369025 -0.22347177 0.1403675 -0.78061169 0.9377669 1.18900581
## [503,] -0.9630409 -0.22347177 0.1403675 -0.98302445 -0.2893481 -1.13939500
## [504,] -0.9630409 -0.22347177 0.1403675 -0.98302445 -0.2893481 -1.13939500
## [505,] 1.0369025 -0.22347177 0.1403675 -0.78061169 0.9377669 1.18900581
## [506,] -0.9630409 -0.22347177 0.1403675 -0.98302445 -0.2893481 -1.13939500
## [507,] -0.9630409 -0.22347177 0.1403675 -0.98302445 -0.2893481 -1.13939500
## [508,] -0.9630409 -0.22347177 0.1403675 -0.98302445 -0.2893481 -1.13939500
## [509,] -0.9630409 -0.22347177 0.1403675 -0.98302445 -0.2893481 -1.13939500
## [510,] -0.9630409 -0.01592015 0.1403675 2.05316689 -1.5164632 0.02480541
## [511,] -0.9630409 -0.01592015 0.1403675 2.05316689 -0.2893481 0.02480541
## [512,] 1.0369025 -0.01592015 0.1403675 2.05316689 -1.5164632 0.02480541
## [513,] -0.9630409 -0.01592015 0.1403675 2.05316689 -0.2893481 0.02480541
## [514,] 1.0369025 -0.01592015 0.1403675 2.05316689 -1.5164632 0.02480541
## [515,] -0.9630409 -0.01592015 0.1403675 2.05316689 -0.2893481 0.02480541
## [516,] -0.9630409 -0.01592015 0.1403675 2.05316689 -0.2893481 0.02480541
## [517,] -0.9630409 -0.01592015 0.1403675 2.05316689 -1.5164632 0.02480541
## [518,] 1.0369025 -0.01592015 0.1403675 2.05316689 -1.5164632 0.02480541
## [519,] -0.9630409 -0.01592015 0.1403675 2.05316689 -0.2893481 0.02480541
## [520,] 1.0369025 0.08785566 0.1403675 1.44592862 -0.2893481 -1.13939500
## [521,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [522,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [523,] 1.0369025 0.08785566 0.1403675 0.83869035 -0.2893481 2.35320621
## [524,] -0.9630409 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [525,] -0.9630409 0.08785566 0.1403675 1.44592862 -0.2893481 -1.13939500
## [526,] 1.0369025 0.08785566 0.1403675 1.44592862 -0.2893481 -1.13939500
## [527,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [528,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [529,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [530,] -0.9630409 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [531,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [532,] -0.9630409 0.08785566 0.1403675 1.44592862 -0.2893481 -1.13939500
## [533,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [534,] 1.0369025 0.08785566 0.1403675 1.44592862 -0.2893481 -1.13939500
## [535,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [536,] -0.9630409 0.08785566 0.1403675 1.44592862 -0.2893481 -1.13939500
## [537,] -0.9630409 0.19163147 0.1403675 0.23145209 2.1648819 1.18900581
## [538,] -0.9630409 0.19163147 0.1403675 0.23145209 0.9377669 -1.13939500
## [539,] 1.0369025 0.50295890 0.1403675 2.05316689 -0.2893481 1.18900581
## [540,] 1.0369025 0.60673471 0.1403675 0.83869035 -0.2893481 0.02480541
## [541,] 1.0369025 0.60673471 0.1403675 0.83869035 -0.2893481 0.02480541
## [542,] 1.0369025 0.71051052 0.1403675 1.24351586 0.9377669 0.02480541
## [543,] 1.0369025 0.71051052 0.1403675 1.24351586 0.9377669 0.02480541
## [544,] 1.0369025 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [545,] -0.9630409 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [546,] -0.9630409 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [547,] 1.0369025 0.71051052 0.1403675 1.24351586 0.9377669 0.02480541
## [548,] 1.0369025 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [549,] -0.9630409 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [550,] -0.9630409 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [551,] 1.0369025 0.71051052 0.1403675 1.24351586 0.9377669 0.02480541
## [552,] 1.0369025 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [553,] -0.9630409 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [554,] 1.0369025 0.71051052 0.1403675 1.24351586 0.9377669 0.02480541
## [555,] -0.9630409 0.71051052 0.1403675 1.24351586 0.9377669 0.02480541
## [556,] -0.9630409 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [557,] 1.0369025 0.71051052 0.1403675 1.24351586 0.9377669 0.02480541
## [558,] 1.0369025 0.71051052 0.1403675 1.24351586 0.9377669 0.02480541
## [559,] -0.9630409 0.81428633 0.1403675 0.83869035 -0.2893481 -1.13939500
## [560,] -0.9630409 1.02183795 1.4757555 1.24351586 0.9377669 0.02480541
## [561,] 1.0369025 1.02183795 1.4757555 1.24351586 0.9377669 0.02480541
## [562,] 1.0369025 1.02183795 1.4757555 1.24351586 0.9377669 0.02480541
## [563,] 1.0369025 1.02183795 1.4757555 1.24351586 0.9377669 0.02480541
## [564,] 1.0369025 1.02183795 1.4757555 1.24351586 0.9377669 0.02480541
## [565,] -0.9630409 1.02183795 1.4757555 1.24351586 0.9377669 0.02480541
## [566,] -0.9630409 1.22938957 1.4757555 2.05316689 -0.2893481 0.02480541
## [567,] 1.0369025 1.22938957 1.4757555 2.05316689 -1.5164632 0.02480541
## [568,] -0.9630409 1.22938957 1.4757555 2.05316689 -0.2893481 0.02480541
## [569,] 1.0369025 1.22938957 1.4757555 2.05316689 -0.2893481 0.02480541
## [570,] -0.9630409 1.22938957 1.4757555 2.05316689 -0.2893481 0.02480541
## [571,] -0.9630409 1.54071700 1.4757555 0.83869035 -1.5164632 0.02480541
## [572,] -0.9630409 1.54071700 1.4757555 0.83869035 -1.5164632 0.02480541
## [573,] -0.9630409 1.85204443 1.4757555 1.04110311 0.9377669 1.18900581
## [574,] -0.9630409 1.85204443 1.4757555 1.04110311 0.9377669 1.18900581
## [575,] -0.9630409 1.85204443 1.4757555 1.04110311 0.9377669 1.18900581
## [576,] -0.9630409 1.85204443 1.4757555 1.04110311 0.9377669 1.18900581
## [577,] -0.9630409 2.16337186 1.4757555 1.44592862 -1.5164632 0.02480541
## [578,] -0.9630409 2.16337186 1.4757555 1.44592862 -1.5164632 0.02480541
## [579,] 1.0369025 2.16337186 1.4757555 1.44592862 -1.5164632 2.35320621
## [580,] -0.9630409 2.16337186 1.4757555 1.44592862 -1.5164632 0.02480541
## [581,] -0.9630409 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [582,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [583,] -0.9630409 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [584,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [585,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [586,] -0.9630409 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [587,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [588,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [589,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [590,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [591,] -0.9630409 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [592,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [593,] -0.9630409 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [594,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [595,] 1.0369025 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [596,] -0.9630409 -0.84612663 -1.1950205 -0.37578618 -0.2893481 0.02480541
## [597,] -0.9630409 -0.84612663 -1.1950205 -0.37578618 -0.2893481 0.02480541
## [598,] 1.0369025 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [599,] -0.9630409 -0.84612663 -1.1950205 -0.37578618 -0.2893481 0.02480541
## [600,] -0.9630409 -0.84612663 -1.1950205 -0.37578618 -0.2893481 0.02480541
## [601,] 1.0369025 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [602,] 1.0369025 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [603,] 1.0369025 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [604,] 1.0369025 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [605,] -0.9630409 -0.84612663 -1.1950205 -0.37578618 -0.2893481 0.02480541
## [606,] 1.0369025 -0.94990244 -1.1950205 -0.78061169 -0.2893481 -1.13939500
## [607,] -0.9630409 -0.74235082 -1.1950205 -0.17337343 0.9377669 0.02480541
## [608,] 1.0369025 -0.53479920 0.1403675 0.83869035 2.1648819 0.02480541
## [609,] -0.9630409 -0.32724758 0.1403675 -0.37578618 -0.2893481 1.18900581
## [610,] 1.0369025 -0.01592015 0.1403675 2.05316689 -0.2893481 0.02480541
## [611,] -0.9630409 0.08785566 0.1403675 1.44592862 -0.2893481 -1.13939500
## [612,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [613,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [614,] 1.0369025 0.08785566 0.1403675 1.44592862 -0.2893481 -1.13939500
## [615,] -0.9630409 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [616,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [617,] -0.9630409 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [618,] -0.9630409 0.08785566 0.1403675 0.83869035 0.9377669 2.35320621
## [619,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [620,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [621,] 1.0369025 0.08785566 0.1403675 0.83869035 0.9377669 2.35320621
## [622,] -0.9630409 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [623,] -0.9630409 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [624,] -0.9630409 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [625,] -0.9630409 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [626,] -0.9630409 0.08785566 0.1403675 0.83869035 0.9377669 2.35320621
## [627,] -0.9630409 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [628,] -0.9630409 0.19163147 0.1403675 0.23145209 2.1648819 1.18900581
## [629,] -0.9630409 0.50295890 0.1403675 1.64834137 0.9377669 -1.13939500
## [630,] -0.9630409 0.60673471 0.1403675 1.04110311 -0.2893481 0.02480541
## [631,] -0.9630409 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [632,] 1.0369025 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [633,] -0.9630409 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [634,] 1.0369025 0.71051052 0.1403675 1.24351586 0.9377669 0.02480541
## [635,] -0.9630409 0.71051052 0.1403675 1.24351586 0.9377669 0.02480541
## [636,] -0.9630409 0.71051052 0.1403675 1.24351586 0.9377669 0.02480541
## [637,] -0.9630409 0.71051052 0.1403675 1.24351586 0.9377669 1.18900581
## [638,] 1.0369025 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [639,] -0.9630409 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [640,] 1.0369025 0.71051052 0.1403675 1.24351586 0.9377669 0.02480541
## [641,] 1.0369025 0.81428633 1.4757555 1.44592862 -1.5164632 -1.13939500
## [642,] -0.9630409 1.02183795 1.4757555 1.24351586 0.9377669 0.02480541
## [643,] 1.0369025 1.02183795 1.4757555 1.24351586 0.9377669 0.02480541
## [644,] -0.9630409 1.02183795 1.4757555 1.24351586 0.9377669 0.02480541
## [645,] -0.9630409 1.02183795 1.4757555 1.24351586 -0.2893481 0.02480541
## [646,] 1.0369025 1.12561376 1.4757555 1.64834137 -1.5164632 2.35320621
## [647,] -0.9630409 1.12561376 1.4757555 1.64834137 -1.5164632 2.35320621
## [648,] 1.0369025 1.12561376 1.4757555 1.64834137 -1.5164632 2.35320621
## [649,] -0.9630409 1.12561376 1.4757555 1.64834137 -1.5164632 2.35320621
## [650,] -0.9630409 1.12561376 1.4757555 1.85075413 -0.2893481 1.18900581
## [651,] 1.0369025 1.22938957 1.4757555 2.05316689 -1.5164632 0.02480541
## [652,] 1.0369025 1.22938957 1.4757555 2.05316689 -1.5164632 0.02480541
## [653,] 1.0369025 1.22938957 1.4757555 2.05316689 -1.5164632 0.02480541
## [654,] 1.0369025 1.22938957 1.4757555 0.23145209 -0.2893481 0.02480541
## [655,] 1.0369025 1.22938957 1.4757555 2.05316689 -1.5164632 0.02480541
## [656,] -0.9630409 1.22938957 1.4757555 2.05316689 -1.5164632 0.02480541
## [657,] 1.0369025 1.22938957 1.4757555 2.05316689 -1.5164632 0.02480541
## [658,] -0.9630409 1.22938957 1.4757555 2.05316689 -1.5164632 0.02480541
## [659,] -0.9630409 1.22938957 1.4757555 2.05316689 -1.5164632 0.02480541
## [660,] -0.9630409 1.22938957 1.4757555 2.05316689 -1.5164632 0.02480541
## [661,] -0.9630409 1.33316538 1.4757555 2.05316689 0.9377669 1.18900581
## [662,] -0.9630409 1.64449281 1.4757555 1.04110311 -1.5164632 0.02480541
## [663,] -0.9630409 1.64449281 1.4757555 0.63627760 -0.2893481 1.18900581
## [664,] 1.0369025 1.74826862 1.4757555 1.24351586 0.9377669 -1.13939500
## [665,] 1.0369025 1.74826862 1.4757555 0.63627760 -0.2893481 0.02480541
## [666,] 1.0369025 1.85204443 1.4757555 2.05316689 -0.2893481 -1.13939500
## [667,] 1.0369025 2.16337186 1.4757555 1.44592862 -1.5164632 2.35320621
## [668,] -0.9630409 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [669,] -0.9630409 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [670,] -0.9630409 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [671,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [672,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [673,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [674,] -0.9630409 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [675,] -0.9630409 0.08785566 0.1403675 1.44592862 -0.2893481 -1.13939500
## [676,] -0.9630409 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [677,] -0.9630409 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [678,] -0.9630409 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [679,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [680,] 1.0369025 0.08785566 0.1403675 1.44592862 -0.2893481 -1.13939500
## [681,] 1.0369025 0.08785566 0.1403675 1.44592862 -0.2893481 -1.13939500
## [682,] -0.9630409 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [683,] -0.9630409 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [684,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [685,] -0.9630409 0.71051052 0.1403675 2.05316689 0.9377669 -1.13939500
## [686,] -0.9630409 0.19163147 0.1403675 -0.37578618 0.9377669 0.02480541
## [687,] 1.0369025 1.02183795 1.4757555 1.24351586 0.9377669 0.02480541
## [688,] 1.0369025 1.22938957 1.4757555 2.05316689 -1.5164632 0.02480541
## [689,] -0.9630409 1.22938957 1.4757555 2.05316689 -0.2893481 0.02480541
## [690,] -0.9630409 -0.43102339 0.1403675 -0.37578618 0.9377669 0.02480541
## [691,] -0.9630409 -0.53479920 0.1403675 0.83869035 2.1648819 0.02480541
## [692,] 1.0369025 -0.01592015 0.1403675 2.05316689 -0.2893481 0.02480541
## [693,] 1.0369025 -0.01592015 0.1403675 0.02903933 -1.5164632 1.18900581
## [694,] 1.0369025 -0.53479920 0.1403675 -0.57819894 -0.2893481 1.18900581
## [695,] -0.9630409 0.08785566 0.1403675 0.83869035 -0.2893481 2.35320621
## [696,] 1.0369025 1.02183795 1.4757555 1.64834137 0.9377669 2.35320621
## [697,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [698,] -0.9630409 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [699,] 1.0369025 2.88980253 2.8111434 0.83869035 0.9377669 -1.13939500
## [700,] -0.9630409 1.74826862 1.4757555 0.63627760 2.1648819 -1.13939500
## [701,] -0.9630409 1.85204443 1.4757555 1.24351586 0.9377669 0.02480541
## [702,] 1.0369025 0.08785566 0.1403675 1.44592862 -1.5164632 -1.13939500
## [703,] -0.9630409 1.12561376 1.4757555 1.64834137 -0.2893481 0.02480541
## [704,] 1.0369025 -0.84612663 -1.1950205 -0.17337343 -0.2893481 -1.13939500
## edadvehiculo antigcarnet kilometros
## [1,] -0.357979046 -1.38660639 -0.339697024
## [2,] -0.451378443 -1.38660639 -0.471752194
## [3,] -0.451378443 -1.38660639 -0.471752194
## [4,] -0.451378443 -1.38660639 -0.471752194
## [5,] -0.451378443 -1.38660639 -0.471752194
## [6,] -0.451378443 -1.38660639 -0.471752194
## [7,] -0.248169091 -1.38660639 -0.259564012
## [8,] -0.083486541 -1.38660639 -0.051688674
## [9,] 0.017789433 -1.38660639 0.012873291
## [10,] 0.028066754 -1.38660639 0.116120159
## [11,] -0.775388066 -1.38660639 -0.678880720
## [12,] -0.775388066 -1.38660639 -0.678880720
## [13,] -0.775388066 -1.38660639 -0.678880720
## [14,] -0.775388066 -1.38660639 -0.678880720
## [15,] -0.775388066 -1.38660639 -0.678880720
## [16,] -0.767377286 -1.28343889 -0.777889425
## [17,] -0.767377286 -1.28343889 -0.777889425
## [18,] -0.492893092 -1.38660639 -0.471248096
## [19,] -0.431415720 -1.38660639 -0.378195223
## [20,] -0.169976544 -1.38660639 -0.138879066
## [21,] -0.169976544 -1.38660639 -0.138879066
## [22,] -0.169976544 -1.38660639 -0.138879066
## [23,] -0.169976544 -1.38660639 -0.138879066
## [24,] -0.169976544 -1.38660639 -0.138879066
## [25,] 2.187231502 -1.18027139 2.187592119
## [26,] -0.437488275 -0.97393639 -0.520089652
## [27,] -0.260465200 -0.56126638 -0.264679680
## [28,] -0.823436708 -1.38660639 -0.820327061
## [29,] -0.823436708 -1.38660639 -0.820327061
## [30,] -0.823436708 -1.38660639 -0.820327061
## [31,] -0.823436708 -1.38660639 -0.820327061
## [32,] -0.823436708 -1.38660639 -0.820327061
## [33,] -0.823436708 -1.38660639 -0.820327061
## [34,] 2.187231502 -1.18027139 2.187592119
## [35,] -0.533392896 -1.38660639 -0.515851489
## [36,] -0.533392896 -1.38660639 -0.515851489
## [37,] -0.533392896 -1.38660639 -0.515851489
## [38,] 0.175592356 -1.38660639 0.232193536
## [39,] 0.175592356 -1.38660639 0.232193536
## [40,] -0.533392896 -1.38660639 -0.515851489
## [41,] 0.175592356 -1.38660639 0.232193536
## [42,] 0.175592356 -1.38660639 0.232193536
## [43,] 0.175592356 -1.38660639 0.232193536
## [44,] 0.175592356 -1.38660639 0.232193536
## [45,] 0.175592356 -1.38660639 0.232193536
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## [667,] 2.187231502 2.22425617 2.085857547
## [668,] -0.841087690 2.74009368 -0.841331171
## [669,] -0.826560124 2.84326118 -0.812877604
## [670,] -0.797536860 2.94642868 -0.761328851
## [671,] -0.874252459 2.94642868 -0.875983284
## [672,] -0.741605423 2.94642868 -0.741388950
## [673,] -0.827585816 2.74009368 -0.884777005
## [674,] -0.797210637 2.53375867 -0.755260998
## [675,] -0.865670711 0.16090613 -0.901337578
## [676,] -0.858781056 0.05773863 -0.843328895
## [677,] -0.841087690 2.74009368 -0.841331171
## [678,] -0.792122334 0.77991114 -0.837727799
## [679,] -0.781148866 0.05773863 -0.819692271
## [680,] -0.781562325 0.16090613 -0.747792870
## [681,] -0.717484721 0.16090613 -0.717322908
## [682,] -0.678075537 2.84326118 -0.679926258
## [683,] -0.746384144 2.84326118 -0.673709042
## [684,] -0.624243878 0.05773863 -0.652312855
## [685,] -0.624243878 0.77991114 -0.631756833
## [686,] -0.434122365 0.26407363 -0.439303179
## [687,] -0.311782790 1.08941365 -0.350581820
## [688,] -0.071055125 1.08941365 -0.123886800
## [689,] -0.152452071 1.29574865 -0.108670489
## [690,] 0.021706571 -0.35493138 -0.022843030
## [691,] 0.013486375 -0.56126638 0.114663874
## [692,] 0.061023193 0.05773863 0.127807779
## [693,] 1.525264212 -0.04542887 1.487772529
## [694,] 1.738379886 -0.45809888 1.756699813
## [695,] 2.187231502 -0.04542887 2.297000192
## [696,] 2.749526578 1.08941365 2.742175292
## [697,] -0.857090161 0.05773863 -0.782052906
## [698,] -0.750996835 0.16090613 -0.750425385
## [699,] -0.741605423 2.94642868 -0.741388950
## [700,] -0.667650890 1.70841866 -0.668425341
## [701,] -0.574570102 1.81158616 -0.607802813
## [702,] -0.624243878 0.05773863 -0.589375208
## [703,] -0.569293425 1.19258115 -0.549943493
## [704,] -0.685054434 -0.97393639 -0.658679434
## attr(,"scaled:center")
## sexo edad grupedad naños tipovehiculo
## 4.815341e-01 3.215341e+01 1.894886e+00 7.856534e+00 2.235795e+00
## antigvehiculo edadvehiculo antigcarnet kilometros
## 1.978693e+00 3.220343e+00 1.344034e+01 5.332949e+04
## attr(,"scaled:scale")
## sexo edad grupedad naños tipovehiculo
## 5.000141e-01 9.636157e+00 7.488460e-01 4.940400e+00 8.149195e-01
## antigvehiculo edadvehiculo antigcarnet kilometros
## 8.589586e-01 3.556851e+00 9.692975e+00 5.356095e+04#análisis de resultados +++++++++++++++++++++++ #changes “changes” muestra la distancia media al perfil (codebook vector) del nodo más prómimo durante el entrenamiento
plot(som_model, type="changes")
som_model$changes## [,1]
## [1,] 0.024769579
## [2,] 0.024835283
## [3,] 0.024662695
## [4,] 0.024348549
## [5,] 0.024942555
## [6,] 0.024266808
## [7,] 0.024731908
## [8,] 0.025535445
## [9,] 0.025130650
## [10,] 0.024923457
## [11,] 0.024763454
## [12,] 0.024375934
## [13,] 0.024655867
## [14,] 0.024876341
## [15,] 0.024601902
## [16,] 0.024326646
## [17,] 0.024931839
## [18,] 0.024576614
## [19,] 0.024615511
## [20,] 0.024504229
## [21,] 0.024018001
## [22,] 0.024774500
## [23,] 0.025098345
## [24,] 0.025188906
## [25,] 0.025179061
## [26,] 0.024840096
## [27,] 0.024002330
## [28,] 0.024947131
## [29,] 0.024960274
## [30,] 0.024384407
## [31,] 0.023642682
## [32,] 0.023813328
## [33,] 0.023222378
## [34,] 0.023411737
## [35,] 0.023640757
## [36,] 0.023407267
## [37,] 0.023412377
## [38,] 0.023219457
## [39,] 0.023285580
## [40,] 0.023512872
## [41,] 0.023570424
## [42,] 0.023950137
## [43,] 0.023220425
## [44,] 0.023480512
## [45,] 0.023209433
## [46,] 0.023050721
## [47,] 0.023480671
## [48,] 0.023086778
## [49,] 0.023212168
## [50,] 0.023666106
## [51,] 0.023261008
## [52,] 0.023044355
## [53,] 0.023330254
## [54,] 0.023657301
## [55,] 0.023021773
## [56,] 0.023666893
## [57,] 0.023302789
## [58,] 0.023052484
## [59,] 0.023032182
## [60,] 0.023267872
## [61,] 0.023217260
## [62,] 0.023056162
## [63,] 0.023363241
## [64,] 0.023791325
## [65,] 0.023510167
## [66,] 0.023030137
## [67,] 0.023622181
## [68,] 0.023790836
## [69,] 0.023587465
## [70,] 0.023510627
## [71,] 0.023316446
## [72,] 0.023996869
## [73,] 0.023754087
## [74,] 0.023623100
## [75,] 0.022973661
## [76,] 0.023305128
## [77,] 0.023094034
## [78,] 0.023199353
## [79,] 0.023033870
## [80,] 0.022791067
## [81,] 0.023216658
## [82,] 0.023405978
## [83,] 0.022930361
## [84,] 0.023629013
## [85,] 0.023430246
## [86,] 0.023191715
## [87,] 0.023573441
## [88,] 0.023457222
## [89,] 0.023438993
## [90,] 0.023500977
## [91,] 0.023514789
## [92,] 0.023200165
## [93,] 0.023449227
## [94,] 0.023008378
## [95,] 0.023881787
## [96,] 0.023664745
## [97,] 0.023706423
## [98,] 0.023723670
## [99,] 0.023637137
## [100,] 0.023043948
## [101,] 0.023224396
## [102,] 0.023039410
## [103,] 0.023268344
## [104,] 0.023063342
## [105,] 0.023994354
## [106,] 0.023394460
## [107,] 0.024065647
## [108,] 0.023258543
## [109,] 0.023418619
## [110,] 0.022997465
## [111,] 0.023030455
## [112,] 0.023531427
## [113,] 0.023260307
## [114,] 0.023387909
## [115,] 0.022669006
## [116,] 0.023242429
## [117,] 0.023250977
## [118,] 0.022936635
## [119,] 0.023210185
## [120,] 0.022585898
## [121,] 0.023152101
## [122,] 0.022995364
## [123,] 0.023257591
## [124,] 0.023452675
## [125,] 0.023181277
## [126,] 0.022975465
## [127,] 0.023180168
## [128,] 0.023328366
## [129,] 0.021817401
## [130,] 0.021651073
## [131,] 0.022209848
## [132,] 0.022242433
## [133,] 0.021804843
## [134,] 0.021970256
## [135,] 0.022373741
## [136,] 0.021599377
## [137,] 0.021759653
## [138,] 0.021666733
## [139,] 0.021960793
## [140,] 0.022428539
## [141,] 0.021016225
## [142,] 0.021919498
## [143,] 0.022664796
## [144,] 0.022063636
## [145,] 0.022220975
## [146,] 0.021790397
## [147,] 0.021961028
## [148,] 0.021230798
## [149,] 0.021633594
## [150,] 0.021623460
## [151,] 0.020989782
## [152,] 0.020815684
## [153,] 0.021396720
## [154,] 0.021296979
## [155,] 0.021198831
## [156,] 0.021201617
## [157,] 0.021155951
## [158,] 0.021169036
## [159,] 0.021097241
## [160,] 0.021797370
## [161,] 0.021500574
## [162,] 0.021598762
## [163,] 0.021337199
## [164,] 0.021216554
## [165,] 0.021734728
## [166,] 0.021186624
## [167,] 0.020854663
## [168,] 0.020935760
## [169,] 0.021112978
## [170,] 0.021289105
## [171,] 0.022055827
## [172,] 0.020738783
## [173,] 0.021493157
## [174,] 0.020642068
## [175,] 0.020977897
## [176,] 0.021611915
## [177,] 0.021598944
## [178,] 0.021028097
## [179,] 0.021813147
## [180,] 0.021260530
## [181,] 0.021215468
## [182,] 0.021297246
## [183,] 0.020696593
## [184,] 0.020913340
## [185,] 0.021015781
## [186,] 0.021240780
## [187,] 0.021314181
## [188,] 0.021235519
## [189,] 0.020933617
## [190,] 0.021096768
## [191,] 0.021173125
## [192,] 0.021274595
## [193,] 0.020791296
## [194,] 0.021220668
## [195,] 0.020904292
## [196,] 0.021627444
## [197,] 0.020842717
## [198,] 0.021833512
## [199,] 0.021483636
## [200,] 0.021565116
## [201,] 0.021043749
## [202,] 0.021237737
## [203,] 0.020957078
## [204,] 0.021260654
## [205,] 0.020857102
## [206,] 0.021152175
## [207,] 0.021750640
## [208,] 0.021123755
## [209,] 0.020069279
## [210,] 0.019841622
## [211,] 0.020167135
## [212,] 0.019754632
## [213,] 0.020480634
## [214,] 0.019857081
## [215,] 0.020469894
## [216,] 0.019708908
## [217,] 0.020672284
## [218,] 0.020235325
## [219,] 0.020175831
## [220,] 0.020457815
## [221,] 0.019759190
## [222,] 0.019982574
## [223,] 0.020111563
## [224,] 0.020018837
## [225,] 0.020438380
## [226,] 0.020461782
## [227,] 0.020029837
## [228,] 0.020400380
## [229,] 0.020224676
## [230,] 0.020549701
## [231,] 0.020560262
## [232,] 0.020263339
## [233,] 0.020422435
## [234,] 0.020317931
## [235,] 0.019504365
## [236,] 0.020407005
## [237,] 0.019888454
## [238,] 0.020449634
## [239,] 0.020461491
## [240,] 0.019793237
## [241,] 0.020482354
## [242,] 0.020190388
## [243,] 0.021142318
## [244,] 0.020109996
## [245,] 0.020740980
## [246,] 0.019764678
## [247,] 0.019682661
## [248,] 0.019475938
## [249,] 0.019700899
## [250,] 0.020306101
## [251,] 0.019580324
## [252,] 0.019276553
## [253,] 0.019967779
## [254,] 0.019524338
## [255,] 0.018348541
## [256,] 0.018665449
## [257,] 0.018571209
## [258,] 0.018016818
## [259,] 0.018035522
## [260,] 0.018801768
## [261,] 0.018196582
## [262,] 0.018148315
## [263,] 0.017708827
## [264,] 0.018339160
## [265,] 0.018354107
## [266,] 0.018815536
## [267,] 0.018129809
## [268,] 0.017953799
## [269,] 0.017977153
## [270,] 0.018407027
## [271,] 0.017947920
## [272,] 0.018131294
## [273,] 0.017981851
## [274,] 0.018440070
## [275,] 0.018069900
## [276,] 0.018511834
## [277,] 0.018206917
## [278,] 0.017903388
## [279,] 0.018605422
## [280,] 0.018287472
## [281,] 0.017810277
## [282,] 0.018093694
## [283,] 0.018165039
## [284,] 0.018043833
## [285,] 0.018279891
## [286,] 0.018215610
## [287,] 0.018182001
## [288,] 0.017919302
## [289,] 0.018534801
## [290,] 0.017825826
## [291,] 0.018596858
## [292,] 0.017876334
## [293,] 0.018291259
## [294,] 0.018011702
## [295,] 0.018383688
## [296,] 0.018239260
## [297,] 0.018207521
## [298,] 0.018048216
## [299,] 0.017911965
## [300,] 0.018245945
## [301,] 0.018174233
## [302,] 0.018121926
## [303,] 0.017580207
## [304,] 0.018186860
## [305,] 0.018006559
## [306,] 0.018536664
## [307,] 0.018013581
## [308,] 0.018093458
## [309,] 0.018056545
## [310,] 0.018276251
## [311,] 0.018028218
## [312,] 0.017638834
## [313,] 0.018150373
## [314,] 0.017907818
## [315,] 0.017669113
## [316,] 0.018302900
## [317,] 0.018320460
## [318,] 0.017758693
## [319,] 0.018094552
## [320,] 0.017933264
## [321,] 0.017604387
## [322,] 0.018307847
## [323,] 0.017616739
## [324,] 0.018295849
## [325,] 0.018281230
## [326,] 0.018236947
## [327,] 0.018359593
## [328,] 0.018309131
## [329,] 0.018707348
## [330,] 0.018613368
## [331,] 0.018164539
## [332,] 0.017848536
## [333,] 0.018229800
## [334,] 0.018149915
## [335,] 0.017982392
## [336,] 0.018248699
## [337,] 0.018255604
## [338,] 0.018272168
## [339,] 0.017076155
## [340,] 0.016536788
## [341,] 0.016339829
## [342,] 0.016156395
## [343,] 0.016235072
## [344,] 0.016065977
## [345,] 0.015991544
## [346,] 0.016100345
## [347,] 0.016035718
## [348,] 0.015930314
## [349,] 0.016147553
## [350,] 0.016120947
## [351,] 0.015963715
## [352,] 0.015703820
## [353,] 0.015786208
## [354,] 0.016025181
## [355,] 0.015711381
## [356,] 0.015765777
## [357,] 0.015805207
## [358,] 0.015652495
## [359,] 0.015681672
## [360,] 0.015818069
## [361,] 0.016374464
## [362,] 0.015677195
## [363,] 0.015466297
## [364,] 0.016398634
## [365,] 0.015787096
## [366,] 0.015550775
## [367,] 0.015925340
## [368,] 0.016563900
## [369,] 0.016128591
## [370,] 0.016287299
## [371,] 0.016168596
## [372,] 0.015667859
## [373,] 0.016454889
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## [375,] 0.014512507
## [376,] 0.014219559
## [377,] 0.013956477
## [378,] 0.013532154
## [379,] 0.013617298
## [380,] 0.013702148
## [381,] 0.013408925
## [382,] 0.013867735
## [383,] 0.013926756
## [384,] 0.013056898
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## [386,] 0.013700952
## [387,] 0.013716087
## [388,] 0.013656422
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## [390,] 0.013506515
## [391,] 0.013653397
## [392,] 0.013528274
## [393,] 0.013590227
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## [395,] 0.013490170
## [396,] 0.013620954
## [397,] 0.013661468
## [398,] 0.013988689
## [399,] 0.013628091
## [400,] 0.013431685
## [401,] 0.013261171
## [402,] 0.013781019
## [403,] 0.014107761
## [404,] 0.014089347
## [405,] 0.014165662
## [406,] 0.013627959
## [407,] 0.013879628
## [408,] 0.013836908
## [409,] 0.013951477
## [410,] 0.013782660
## [411,] 0.013841028
## [412,] 0.013728093
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## [414,] 0.014099423
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## [418,] 0.013413622
## [419,] 0.014095863
## [420,] 0.013850616
## [421,] 0.013794691
## [422,] 0.013497027
## [423,] 0.013624652
## [424,] 0.013890889
## [425,] 0.013806785
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## [427,] 0.014126529
## [428,] 0.013793656
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## [466,] 0.013633080
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## [483,] 0.009154906
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## [485,] 0.008685215
## [486,] 0.008946445
## [487,] 0.008487829
## [488,] 0.008618157
## [489,] 0.008781692
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## [505,] 0.008184252
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## [507,] 0.007791011
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## [511,] 0.008317540
## [512,] 0.008279833
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## [533,] 0.008039104
## [534,] 0.007926000
## [535,] 0.008023466
## [536,] 0.007693014
## [537,] 0.008247244
## [538,] 0.008061579
## [539,] 0.008207141
## [540,] 0.008016079
## [541,] 0.007811122
## [542,] 0.007883258
## [543,] 0.007629131
## [544,] 0.008299508
## [545,] 0.007857451
## [546,] 0.008064817
## [547,] 0.008128086
## [548,] 0.007985387
## [549,] 0.007748886
## [550,] 0.007586795
## [551,] 0.008203770
## [552,] 0.008216280
## [553,] 0.007834670
## [554,] 0.007939418
## [555,] 0.008053370
## [556,] 0.008143263
## [557,] 0.007359086
## [558,] 0.008006766
## [559,] 0.007859040
## [560,] 0.008048544
## [561,] 0.007595712
## [562,] 0.007849472
## [563,] 0.007717073
## [564,] 0.007904957
## [565,] 0.008271402
## [566,] 0.007935493
## [567,] 0.008097399
## [568,] 0.008063244
## [569,] 0.008322750
## [570,] 0.008010084
## [571,] 0.007953343
## [572,] 0.008091863
## [573,] 0.008010851
## [574,] 0.007483566
## [575,] 0.007839256
## [576,] 0.008019360
## [577,] 0.007648515
## [578,] 0.007808782
## [579,] 0.007868240
## [580,] 0.007917165
## [581,] 0.007754027
## [582,] 0.007849005
## [583,] 0.008029254
## [584,] 0.008451481
## [585,] 0.007870575
## [586,] 0.007844188
## [587,] 0.007992851
## [588,] 0.007974345
## [589,] 0.007974879
## [590,] 0.008311491
## [591,] 0.007910466
## [592,] 0.007865450
## [593,] 0.008060400
## [594,] 0.007798885
## [595,] 0.008346983
## [596,] 0.007774328
## [597,] 0.007616889
## [598,] 0.007693214
## [599,] 0.008193073
## [600,] 0.007964366#“count” " count"muestra el número de instancias asignada a cada nodo los nodos vacíos aparecen en gris
plot(som_model, type="count", main="instancias por nodo")
“dist.neighbours”
“dist.neighbours” muestra la suma de las distancias( entre perfiles) a todos los vecinos inmediatos. Esta visualización también se conoce como gráfico de la matriz U
plot(som_model, type="dist.neighbours", main = " distancias
a los perfiles vecinos") 
# “codes”
“codes” permite visualizar ( si hay pocas variables)los valores que toma para cada variable cada perfil de cada nodo También pueden listarse los valores de cada variable en cada perfil
plot(som_model, type="codes")
som_model$codes## [[1]]
## sexo edad grupedad naños tipovehiculo antigvehiculo
## V1 -0.96304094 -0.22347182 -1.19502048 -1.3878500 -0.28934815 2.35320621
## V2 -0.96304066 0.43803050 0.14036730 0.3264325 -0.09740987 2.35320617
## V3 1.03690247 0.35104594 0.26797339 0.7074690 0.17334501 2.24025317
## V4 0.41885260 1.54925681 1.47572382 1.5657115 -1.51607505 2.35317925
## V5 1.03690162 1.17714712 1.47575544 1.9767429 -1.39019941 -0.12171396
## V6 -0.96304093 1.54612854 1.47575546 1.5128372 -1.51646320 -0.22066881
## V7 1.03224955 1.77662234 1.47721547 1.2233123 0.12684240 -0.68238862
## V8 0.10157739 2.88980253 2.81114342 0.8386904 0.93776690 -1.13939500
## V9 1.03690249 -0.84439632 -1.19502048 -1.3375049 -0.07029756 2.35320621
## V10 -0.96276340 -0.94864900 -0.39668649 -1.0872328 0.13697967 2.35310054
## V11 1.03370195 0.39827256 0.14003289 -0.5768956 -0.28906106 1.19072944
## V12 -0.96294571 0.33018014 0.14041489 0.4842570 -0.01373007 2.35314148
## V13 -0.96303865 1.63969081 1.47575478 1.2555524 0.59548633 1.18900574
## V14 -0.96302293 1.17946832 1.47575372 1.8584126 -0.28934917 0.02480757
## V15 -0.96304074 1.18730828 1.47575523 0.8345661 0.93776641 0.02480537
## V16 -0.96304093 1.36967780 1.47575545 -0.2867652 2.16488191 -0.07759750
## V17 1.03690249 -0.94990244 -1.19502048 -0.5781989 -0.28934815 1.18900581
## V18 1.03591604 -0.34236151 0.13961584 -0.3918146 -0.56746191 1.18907741
## V19 -0.96304093 -0.11661043 0.14036747 -0.5793069 -0.41681837 1.18900581
## V20 -0.96107677 0.36021946 0.14158751 0.5587174 1.76450994 1.18823147
## V21 1.03690249 0.83712313 0.68345151 1.2435159 0.93776690 0.02480541
## V22 0.11790954 0.74575211 0.56381977 0.8121296 0.84887426 -0.29956388
## V23 -0.96304094 0.55366381 0.14036749 0.4786995 0.93776690 0.02480541
## V24 -0.96304094 0.47921182 0.14119169 0.2313482 0.93837080 0.02245800
## V25 1.03690249 -0.89622093 -1.19502048 -0.5781989 -0.28934815 1.18900581
## V26 0.67439265 -1.07503909 -1.13951375 -0.8712812 -0.28962036 0.68037007
## V27 -0.96304094 -0.92169935 -1.19502048 -0.5781989 -0.28934815 1.18900581
## V28 1.03382381 -0.22400740 0.13961079 -0.5492645 0.93884465 1.18620956
## V29 0.94482429 0.26947687 0.32141667 0.2883641 1.39465330 -0.14048174
## V30 1.03690249 0.69892406 0.56153939 0.7128928 0.93776690 -1.13939500
## V31 -0.43277611 0.58181926 0.25209945 0.4427476 0.75640098 -0.77123954
## V32 -0.96304094 0.47659948 0.14036749 0.2287053 0.93776690 -1.13939500
## V33 1.03690249 -1.42232843 -1.19502048 -1.3569363 -0.20858676 0.02480541
## V34 1.03690249 -1.00162401 -1.19502048 -1.0233772 -0.28934815 0.02480541
## V35 0.88104564 -0.45463726 0.07648311 -1.0555929 1.03947889 0.04901923
## V36 1.03690249 -0.43415274 0.14036749 -0.3391638 2.16488194 0.02480541
## V37 1.03690249 0.50295890 0.14036749 0.2314521 0.93776690 0.02480541
## V38 0.39770660 0.62617089 0.35033696 0.3716481 0.26746047 -0.37400619
## V39 -0.96304094 0.53118729 0.14036749 0.2865110 -0.28934815 -1.13939500
## V40 -0.96304094 0.69191167 0.14036749 2.0168902 0.93776690 -1.13939500
## V41 1.03690249 -1.23021385 -1.19502048 -1.2017213 -1.51646320 0.02480541
## V42 1.03690249 -0.94184443 -1.19502048 -0.7334607 -0.28934815 -1.13939500
## V43 -0.96247649 -0.81415594 -1.19465598 0.1059048 0.93742359 -0.78021016
## V44 -0.96304094 -0.43602105 0.14036749 -0.3172992 2.16488194 0.02480541
## V45 0.62972298 0.02443426 0.19894280 -0.1035118 1.28117528 0.01218000
## V46 1.03690244 1.14826616 1.47542600 -0.7157979 -0.28934812 0.02480540
## V47 -0.96304094 0.71900712 0.60371920 -0.1899459 -0.71513142 0.02480541
## V48 -0.96304094 0.07559516 0.14036749 1.7071515 -0.28934815 -0.49885623
## V49 -0.96304075 -1.22027170 -1.19502048 -1.3186051 -1.51646304 -1.13939480
## V50 -0.96304094 -1.15565800 -1.19502048 -1.0442221 -0.28934815 -1.13939500
## V51 -0.96304094 -0.24252697 0.14036748 -1.0016078 -0.42997737 -1.13939499
## V52 -0.95750464 -0.13976883 0.14036747 -0.3776264 0.90470512 0.01569044
## V53 1.03690249 0.48130520 0.14036749 0.3181007 -0.28934815 0.02480541
## V54 1.03689886 -0.25792625 0.14036842 -0.2004135 -1.51645459 0.02480483
## V55 0.04890279 0.18291872 0.18932122 1.1360420 -0.98236948 -0.71630591
## V56 -0.96304094 0.07322991 0.14036749 1.5315103 -1.51646320 -0.97531726
## V57 -0.96304094 -1.21794840 -1.19502048 -1.1921519 -1.51646320 0.02480541
## V58 -0.96304094 -1.00048500 -1.19502048 -0.7846567 -0.28934815 0.02480541
## V59 -0.96304094 -0.62721611 -0.32834241 -0.7571646 -0.54947968 -0.58778519
## V60 -0.96304094 -0.43102339 0.14036749 -0.3757862 -0.28934815 0.02480541
## V61 -0.17759402 -0.35117461 0.14036749 -0.4263661 -0.30516664 -0.13393419
## V62 1.03690249 -0.42461594 0.14036749 -0.3724662 -0.28934815 0.02480541
## V63 1.03689708 -0.17392769 0.14036759 -0.1743830 -0.28939710 -1.13934225
## V64 1.03690249 0.09636718 0.14036749 1.5703000 -1.05075959 -0.94865402
## edadvehiculo antigcarnet kilometros
## V1 3.006370435 -0.16827529 2.98495523
## V2 3.030673728 0.50902829 3.04042151
## V3 2.311076980 0.40051663 2.31310076
## V4 2.219071139 1.57934845 2.20440721
## V5 -0.170367514 1.15183598 -0.18548426
## V6 -0.265831471 1.57566232 -0.27770980
## V7 -0.455305484 1.76429801 -0.46771585
## V8 -0.776383639 2.73225474 -0.75865657
## V9 2.509034918 -0.84338139 2.52894970
## V10 2.537942212 -0.90139557 2.52300444
## V11 1.573310723 0.46944401 1.66332131
## V12 1.959945716 0.36225514 1.98542725
## V13 1.065112913 1.55235621 1.05185419
## V14 -0.241853549 1.18048860 -0.24545875
## V15 -0.222167987 1.08236898 -0.23062203
## V16 -0.342753420 1.42613995 -0.28450782
## V17 1.602501303 -0.95919893 1.58060211
## V18 1.730061346 -0.29021318 1.72406473
## V19 0.976513604 -0.05307826 0.96764331
## V20 1.036685588 0.39824696 1.07515405
## V21 -0.249997395 0.86564802 -0.26689087
## V22 -0.306904386 0.76786518 -0.32550179
## V23 0.007184667 0.60455809 -0.02714764
## V24 -0.504191147 0.54985113 -0.57596971
## V25 1.072802665 -0.84408546 1.04373195
## V26 0.801801779 -1.04811341 0.80526716
## V27 1.090537188 -0.90319515 1.06560872
## V28 0.635877746 -0.14938546 0.63411524
## V29 -0.265761919 0.29421678 -0.25217272
## V30 -0.817820590 0.73416745 -0.82264716
## V31 -0.586484636 0.61139676 -0.60209003
## V32 -0.757989782 0.51288364 -0.78244430
## V33 0.165733682 -1.37085003 0.22273432
## V34 -0.348951735 -1.04201754 -0.36900681
## V35 -0.220866539 -0.56472071 -0.22515451
## V36 -0.132467967 -0.42933316 -0.13183770
## V37 -0.350796104 0.55218368 -0.28993272
## V38 -0.457745458 0.66477723 -0.43697789
## V39 -0.741496879 0.55622837 -0.74037181
## V40 -0.765322835 0.75217640 -0.76446314
## V41 -0.437413646 -1.24090479 -0.41351657
## V42 -0.739536588 -1.35456328 -0.86722092
## V43 -0.578312561 -0.97395809 -0.56970051
## V44 -0.231365143 -0.44006591 -0.23146291
## V45 -0.194096001 0.05227518 -0.18679839
## V46 -0.016174258 1.21509011 -0.05404841
## V47 -0.356776554 0.76298910 -0.30893018
## V48 -0.439945609 0.12560259 -0.46836017
## V49 -0.819296489 -1.24543321 -0.73412235
## V50 -0.779631267 -1.30455839 -0.80280141
## V51 -0.748017516 -0.19482966 -0.68933075
## V52 -0.207640530 -0.06755607 -0.23210120
## V53 -0.158505978 0.51515376 -0.15311256
## V54 -0.355268438 -0.23265685 -0.31666226
## V55 -0.593320711 0.20971682 -0.57670584
## V56 -0.725287696 0.12461883 -0.73015087
## V57 -0.130694738 -1.22189094 -0.12741929
## V58 -0.338206099 -1.06646478 -0.35372318
## V59 -0.601591135 -0.62343574 -0.59683610
## V60 -0.307607615 -0.40810494 -0.32313727
## V61 -0.374701442 -0.31727603 -0.38449466
## V62 -0.317786690 -0.41880183 -0.33584200
## V63 -0.759201384 -0.22155645 -0.70098288
## V64 -0.644454857 0.10731877 -0.62220762“property”
“property” evalúa la variable considerada para el perfil obtenido en cada nodo mostrándolo en un mapa de color “property” es el atributo del objeto som del que consideramos los valores numéricos de los perfiles según una sintaxis como: #plot(som_model, type = “property”, property = getCodes(som_model)[,1], main=colnames(getCodes(som_model))[1], palette.name=coolBlueHotRed) el atributo pallete.name es el de la paleta que hemos cargado al principio
plot(som_model, type = "property", property = getCodes(som_model)[,1], main=colnames(getCodes(som_model))[1], palette.name=coolBlueHotRed)
plot(som_model, type = "property", property = getCodes(som_model)[,2], main=colnames(getCodes(som_model))[2], palette.name=coolBlueHotRed)
plot(som_model, type = "property", property = getCodes(som_model)[,3], main=colnames(getCodes(som_model))[3],palette.name=coolBlueHotRed)
plot(som_model, type = "property", property = getCodes(som_model)[,4], main=colnames(getCodes(som_model))[4],palette.name=coolBlueHotRed)
plot(som_model, type = "property", property = getCodes(som_model)[,5], main=colnames(getCodes(som_model))[5],palette.name=coolBlueHotRed)
plot(som_model, type = "property", property = getCodes(som_model)[,6], main=colnames(getCodes(som_model))[6],palette.name=coolBlueHotRed)
plot(som_model, type = "property", property = getCodes(som_model)[,7], main=colnames(getCodes(som_model))[7],palette.name=coolBlueHotRed)
plot(som_model, type = "property", property = getCodes(som_model)[,8], main=colnames(getCodes(som_model))[8],palette.name=coolBlueHotRed)
plot(som_model, type = "property", property = getCodes(som_model)[,9], main=colnames(getCodes(som_model))[9],palette.name=coolBlueHotRed)
para cualquiera de la variables podemos obtener los valores numéricos de cada correspondientes asignando "getCodes(som_model)[,numero_de_la_variable] por ejemplo para las edades ( variable numero 2) de los 64 perfiles: perfiles_de_edad= getCodes(som_model)[,2]*sd(data_train\(edad)+ mean(data_train\)edad) # deshacemos la tipificación
perfiles_de_edad= getCodes(som_model)[,2]*sd(data_train$edad)+ mean(data_train$edad)
perfiles_de_edad## V1 V2 V3 V4 V5 V6 V7 V8
## 30.00000 36.37434 35.53614 47.08229 43.49658 47.05215 49.27322 60.00000
## V9 V10 V11 V12 V13 V14 V15 V16
## 24.01667 23.01208 35.99123 35.33508 47.95373 43.51895 43.59450 45.35184
## V17 V18 V19 V20 V21 V22 V23 V24
## 23.00000 28.85436 31.02973 35.62454 40.22006 39.33959 37.48860 36.77117
## V25 V26 V27 V28 V29 V30 V31 V32
## 23.51728 21.79416 23.27177 29.99484 34.75013 38.88835 37.75991 36.74600
## V33 V34 V35 V36 V37 V38 V39 V40
## 18.44763 22.50160 27.77245 27.96985 37.00000 38.18729 37.27201 38.82078
## V41 V42 V43 V44 V45 V46 V47 V48
## 20.29888 23.07765 24.30807 27.95184 32.38886 43.21828 39.08187 32.88186
## V49 V50 V51 V52 V53 V54 V55 V56
## 20.39468 21.01731 29.81638 30.80657 36.79134 29.66799 33.91604 32.85906
## V57 V58 V59 V60 V61 V62 V63 V64
## 20.41707 22.51258 26.10946 28.00000 28.76944 28.06174 30.47741 33.08202“quality”
“quality” muestra para cada nodo la distancia media de las instancia asignadas al nodo a cada perfil cuanto más pequeñas sean estas disntancias mejor representados estarán las instancia por el perfil al que se le ha hasignado plot(som_model, type=“quality”)
plot(som_model, type="quality")
# “mapping” “mapping” muestra dónde han sido asignados los disntintos individuos o instancia añadiendo intify podemos identificarlos ( en realidad sólo a uno por neurona) posiblemente en Rmarkdown no podrá hacerse la instrucción indentify
plot(som_model, type="mapping")
identify(som_model)
## integer(0)agrupando perfiles
+++++++++++++++++++++++++++++++++++++++++
llegados aquí puede usarse una análisis cluster jerárquico para agrupar los prefiles según su semejanza
(la función “object.distances” calcula las distancias ( por defecto euclidea) entre los perfiles obtenidos en un objeto de clase som )
utilizamos el método de ward
clusperfil<-hclust(object.distances(som_model, "codes"),method="ward.D")
plot(clusperfil)#visualizamos el dendograma
parece que tres o cuatro grupos puede ser una buena agrupación generamos una agrupación de cuatro grupos y añadimos sus FRONTERAS al SOM
#som.hc <- cutree(clusperfil, 4)
podremos usar la instrucción “add.cluster.boundaries” para visualizar las fronteras entre estos grupos #add.cluster.boundaries(som_model, som.hc)
y visualizar todos los gráficos anteriores con estas fronteras
som.hc <- cutree(clusperfil, 4)
plot(som_model, type = "property", property = getCodes(som_model)[,2], main=colnames(getCodes(som_model))[2],palette.name=coolBlueHotRed)
add.cluster.boundaries(som_model,som.hc)
plot(som_model, type = "property", property = getCodes(som_model)[,5], main=colnames(getCodes(som_model))[5],palette.name=coolBlueHotRed)
add.cluster.boundaries(som_model,som.hc)
avanzando hacia el uso del mapa autorganizado para la clasificació
si queremos ver cómo se comportan tanto los perfiles obtenidos en el som como los grupos obtenidos en cuanto a otra variable tipo clase se refiere en nuestro ejemplo podría ser la variable sinUA ( sinisetros en el último año) podremos hacerlo considerando los valores que toman en esta variable las instancias asignadas a cada celda ( nodo o nuerona) y promediándolos
Podemos , después añadir estos promedios al objeto som_model y utilzar plot con la opción “property=getCodes(som_modelNUEVO)[,10]”