Semana 3
2023-06-02
SEMANA 3: ANALISIS DE CORRESPONDENCIAS MULTIPLES
Cargar los datos
datos <- as.data.frame(Base_People_Analytics)
datos <- subset(datos, JobRole=="Sales Executive")
### caracteristicas
datos$Education <- factor(datos$Education,
levels = c(1,2,3,4,5),
labels = c("Bachillerato","Técnico","Pregrado", "MaestrÃa", "Doctorado"))
datos$Age <- cut(datos$Age,
breaks=c(20, 30, 40, 50, 60),
labels=c('20-30 años', '31-40 años', '41-50 años', '51-60 años'))
datos$DistanceFromHome <- cut(datos$DistanceFromHome,
breaks=c(0, 10, 20, 30, 40),
labels=c('1-10 kilómetros', '11-20 kilómetros', '21-30 kilómetros', '31-40 kilómetros'))
datos <- as.matrix(datos[c("BusinessTravel", "EducationField", "Education", "Gender", "MaritalStatus", "Age", "DistanceFromHome")])
datos <- as.data.frame(datos)
head(datos)## BusinessTravel EducationField Education Gender MaritalStatus Age
## 1062 Travel_Rarely Life Sciences Técnico Female Single 41-50 años
## 1063 Travel_Rarely Marketing MaestrÃa Male Married 41-50 años
## 1064 Travel_Frequently Life Sciences Pregrado Female Married 31-40 años
## 1065 Travel_Frequently Life Sciences Pregrado Male Single 20-30 años
## 1066 Non-Travel Marketing MaestrÃa Male Single 31-40 años
## 1067 Travel_Frequently Marketing MaestrÃa Male Single 41-50 años
## DistanceFromHome
## 1062 1-10 kilómetros
## 1063 1-10 kilómetros
## 1064 1-10 kilómetros
## 1065 1-10 kilómetros
## 1066 21-30 kilómetros
## 1067 1-10 kilómetrosAnálisis de correspondencias múltiples
Esta parte exploramos cuales son las variables que se podrian estar asociando entre ellas.
res.mca <- MCA(datos, ncp = 5, graph = TRUE)## Warning: ggrepel: 5 unlabeled data points (too many overlaps). Consider
## increasing max.overlaps
print(res.mca) ### Las variables que se asocian entre ellas## **Results of the Multiple Correspondence Analysis (MCA)**
## The analysis was performed on 326 individuals, described by 7 variables
## *The results are available in the following objects:
##
## name description
## 1 "$eig" "eigenvalues"
## 2 "$var" "results for the variables"
## 3 "$var$coord" "coord. of the categories"
## 4 "$var$cos2" "cos2 for the categories"
## 5 "$var$contrib" "contributions of the categories"
## 6 "$var$v.test" "v-test for the categories"
## 7 "$ind" "results for the individuals"
## 8 "$ind$coord" "coord. for the individuals"
## 9 "$ind$cos2" "cos2 for the individuals"
## 10 "$ind$contrib" "contributions of the individuals"
## 11 "$call" "intermediate results"
## 12 "$call$marge.col" "weights of columns"
## 13 "$call$marge.li" "weights of rows"Identificacion del numero de dimensiones posibles
eig.val <- get_eigenvalue(res.mca)
fviz_screeplot(res.mca, addlabels = TRUE, ylim = c(0, 20)) + geom_hline(yintercept = 7.14, linetype = 2, color = "red")
fviz_mca_biplot(res.mca,
repel = TRUE, # Avoid text overlapping (slow if many point)
ggtheme = theme_minimal())
Analisis de Varianza
var <- get_mca_var(res.mca)
var## Multiple Correspondence Analysis Results for variables
## ===================================================
## Name Description
## 1 "$coord" "Coordinates for categories"
## 2 "$cos2" "Cos2 for categories"
## 3 "$contrib" "contributions of categories"var$contrib## Dim 1 Dim 2 Dim 3 Dim 4
## Non-Travel 2.99907694 4.53605333 2.327494e+01 3.993953e-01
## Travel_Frequently 3.91493810 3.78125250 1.688594e+00 2.126411e-01
## Travel_Rarely 0.08426052 0.01173505 7.056113e+00 7.183010e-04
## Life Sciences 2.22653599 0.07421206 1.775864e+00 9.778477e-01
## Marketing 3.17859931 13.19061061 6.486653e-01 8.022796e-02
## Medical 0.25868045 11.29498181 4.892352e+00 2.417829e-01
## Other 0.05845841 7.45752573 2.416197e+00 4.282444e+00
## Technical Degree 0.05568499 1.88942659 2.835055e+00 1.495116e+01
## Bachillerato 15.75068098 0.40253147 7.986031e+00 5.644274e+00
## Doctorado 3.51609668 8.70914428 5.861503e+00 1.417426e+00
## MaestrÃa 14.02412821 0.02838136 1.011520e+00 1.320548e+01
## Pregrado 3.83379310 1.68605541 1.405766e+00 2.128930e+00
## Técnico 0.06431407 7.90645964 9.366431e-06 1.253044e+01
## Female 2.83516717 3.44732483 7.957017e-01 9.776954e+00
## Male 1.92908281 2.34560246 5.414052e-01 6.652361e+00
## Divorced 7.06612838 1.91362548 1.182719e+01 2.298901e+00
## Married 1.66710359 0.66673777 6.464317e-01 8.428419e-01
## Single 0.36436797 0.02002852 3.294449e+00 5.377943e+00
## 20-30 años 13.79047213 7.90489227 8.975306e-01 5.769230e-01
## 31-40 años 12.14160875 1.02201348 7.460179e-02 6.360687e-02
## 41-50 años 0.26166584 5.48685194 4.878733e-01 7.897330e+00
## 51-60 años 3.33499413 13.23600224 6.346163e-02 7.934129e+00
## 1-10 kilómetros 0.68032960 0.58304135 3.634982e+00 6.500044e-05
## 11-20 kilómetros 5.31783782 2.39903203 3.869201e-03 1.079585e+00
## 21-30 kilómetros 0.64599404 0.00647780 1.687990e+01 1.426586e+00
## Dim 5
## Non-Travel 1.215259310
## Travel_Frequently 13.599474977
## Travel_Rarely 2.016433561
## Life Sciences 0.095000296
## Marketing 1.698285615
## Medical 0.208279666
## Other 3.134117258
## Technical Degree 0.068804865
## Bachillerato 4.120299280
## Doctorado 1.711447026
## MaestrÃa 0.254183845
## Pregrado 11.768611575
## Técnico 4.605030451
## Female 5.350829303
## Male 3.640770454
## Divorced 2.102565282
## Married 8.102091900
## Single 4.961347185
## 20-30 años 0.850175571
## 31-40 años 1.246860679
## 41-50 años 13.490022960
## 51-60 años 2.928685292
## 1-10 kilómetros 2.290627778
## 11-20 kilómetros 0.003966454
## 21-30 kilómetros 10.536829418Coordenadas
head(var$coord)## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## Non-Travel -0.59825572 0.71086544 1.5666925 0.200419255 0.34393102
## Travel_Frequently 0.55572739 -0.52768222 0.3430903 -0.118896172 -0.93541479
## Travel_Rarely -0.04147343 0.01495394 -0.3567690 -0.003515249 0.18322879
## Life Sciences 0.31120627 -0.05489414 0.2612671 -0.189327640 -0.05805502
## Marketing -0.34822772 -0.68538274 -0.1478775 -0.050787081 0.22987652
## Medical 0.13609761 0.86889384 -0.5563831 0.120788720 -0.11028995# Distancia de cada categorÃa al centroide
head(var$cos2)## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## Non-Travel 0.048635841 0.0686684929 0.33354177 5.458353e-03 0.016074053
## Travel_Frequently 0.068243982 0.0615298247 0.02601103 3.123752e-03 0.193352245
## Travel_Rarely 0.004001739 0.0005202597 0.29613040 2.874888e-05 0.078108119
## Life Sciences 0.047319084 0.0014722841 0.03335102 1.751329e-02 0.001646718
## Marketing 0.072519757 0.2809286248 0.01307778 1.542539e-03 0.031602315
## Medical 0.004612898 0.1880209701 0.07709404 3.633504e-03 0.003029317Contribución de cada variable a los componentes principales
head(var$contrib)## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## Non-Travel 2.99907694 4.53605333 23.2749402 0.399395265 1.2152593
## Travel_Frequently 3.91493810 3.78125250 1.6885940 0.212641082 13.5994750
## Travel_Rarely 0.08426052 0.01173505 7.0561128 0.000718301 2.0164336
## Life Sciences 2.22653599 0.07421206 1.7758640 0.977847742 0.0950003
## Marketing 3.17859931 13.19061061 0.6486653 0.080227962 1.6982856
## Medical 0.25868045 11.29498181 4.8923524 0.241782872 0.2082797fviz_mca_var(res.mca, choice = "mca.cor",
repel = TRUE, # Avoid text overlapping (slow)
ggtheme = theme_minimal())
head(round(var$coord, 2), 4)## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## Non-Travel -0.60 0.71 1.57 0.20 0.34
## Travel_Frequently 0.56 -0.53 0.34 -0.12 -0.94
## Travel_Rarely -0.04 0.01 -0.36 0.00 0.18
## Life Sciences 0.31 -0.05 0.26 -0.19 -0.06fviz_mca_var(res.mca,
repel = TRUE, # Avoid text overlapping (slow)
ggtheme = theme_minimal())
fviz_mca_var(res.mca, col.var="black", shape.var = 15,
repel = TRUE)
head(var$cos2, 20)## Dim 1 Dim 2 Dim 3 Dim 4
## Non-Travel 0.0486358412 0.0686684929 3.335418e-01 5.458353e-03
## Travel_Frequently 0.0682439818 0.0615298247 2.601103e-02 3.123752e-03
## Travel_Rarely 0.0040017391 0.0005202597 2.961304e-01 2.874888e-05
## Life Sciences 0.0473190837 0.0014722841 3.335102e-02 1.751329e-02
## Marketing 0.0725197566 0.2809286248 1.307778e-02 1.542539e-03
## Medical 0.0046128977 0.1880209701 7.709404e-02 3.633504e-03
## Other 0.0008692673 0.1035170015 3.174911e-02 5.366461e-02
## Technical Degree 0.0008442100 0.0267394769 3.798103e-02 1.910193e-01
## Bachillerato 0.2451765149 0.0058491117 1.098508e-01 7.404189e-02
## Doctorado 0.0521172966 0.1205055635 7.677554e-02 1.770563e-02
## MaestrÃa 0.2900975600 0.0005480396 1.848995e-02 2.302038e-01
## Pregrado 0.0866188017 0.0355603382 2.806656e-02 4.053542e-02
## Técnico 0.0011512864 0.1321204278 1.481646e-07 1.890312e-01
## Female 0.0680185957 0.0772043443 1.686911e-02 1.976708e-01
## Male 0.0680185957 0.0772043443 1.686911e-02 1.976708e-01
## Divorced 0.1279673336 0.0323508043 1.892744e-01 3.508551e-02
## Married 0.0443379141 0.0165530593 1.519246e-02 1.889073e-02
## Single 0.0077084709 0.0003955373 6.158908e-02 9.588135e-02
## 20-30 años 0.2526947033 0.1352145725 1.453313e-02 8.908912e-03
## 31-40 años 0.3466884316 0.0272414537 1.882371e-03 1.530583e-03
## Dim 5
## Non-Travel 0.0160740530
## Travel_Frequently 0.1933522446
## Travel_Rarely 0.0781081189
## Life Sciences 0.0016467178
## Marketing 0.0316023152
## Medical 0.0030293169
## Other 0.0380109952
## Technical Degree 0.0008507836
## Bachillerato 0.0523113480
## Doctorado 0.0206905555
## MaestrÃa 0.0042884837
## Pregrado 0.2168684352
## Técnico 0.0672353230
## Female 0.1047026573
## Male 0.1047026573
## Divorced 0.0310566568
## Married 0.1757508578
## Single 0.0856081822
## 20-30 años 0.0127061285
## 31-40 años 0.0290381311#Contribución de cada categorÃa a los componentes principales en color
fviz_mca_var(res.mca, col.var = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE, # Avoid text overlapping
ggtheme = theme_minimal())
Contribución de cada categorÃa a los componentes principales (transparencias)
fviz_mca_var(res.mca, alpha.var="cos2",
repel = TRUE,
ggtheme = theme_minimal())
Matrix de Correlaciones
library("corrplot")## corrplot 0.92 loadedcorrplot(var$cos2, is.corr=FALSE)
head(round(var$contrib,2), 4)## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## Non-Travel 3.00 4.54 23.27 0.40 1.22
## Travel_Frequently 3.91 3.78 1.69 0.21 13.60
## Travel_Rarely 0.08 0.01 7.06 0.00 2.02
## Life Sciences 2.23 0.07 1.78 0.98 0.10Caracteristicas de la dimension 1
#Contribución de cada caso a los componentes principales: Dim 1
fviz_contrib(res.mca, choice = "var", axes = 1, top = 15)
Caracteristicas de la dimension 2
#Contribución de cada caso a los componentes principales: Dim 2
fviz_contrib(res.mca, choice = "var", axes = 2, top = 15)
ESTE ES LA GRAFICA PARA HACER LA INTERPRETACION DE LOS PERFILES
fviz_mca_var(res.mca, col.var = "contrib",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE, # avoid text overlapping (slow)
ggtheme = theme_minimal())
Analisis de la contribución de individuos a los perfiles
Este es un segundo analisis para el efecto de los individuos de los perfiles. Sin embargo, con el anterior grafico ya se puede hacer el analisis del ejercicio de la semana
ind <- get_mca_ind(res.mca)
ind## Multiple Correspondence Analysis Results for individuals
## ===================================================
## Name Description
## 1 "$coord" "Coordinates for the individuals"
## 2 "$cos2" "Cos2 for the individuals"
## 3 "$contrib" "contributions of the individuals"ind$contrib## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## 1062 1.606718e-01 4.934261e-03 2.103906e-02 4.387919e-01 4.695304e-02
## 1063 1.297483e-01 2.088576e-01 2.559774e-02 2.078640e-02 3.112260e-02
## 1064 2.647271e-01 1.842493e-01 1.551698e-01 7.742786e-02 1.404686e-01
## 1065 7.468878e-01 4.909954e-03 6.657162e-02 2.263257e-01 1.174663e+00
## 1066 7.100754e-01 2.505246e-02 1.905070e+00 6.617827e-01 2.668188e-01
## 1067 2.802310e-02 4.055931e-01 6.049094e-02 2.216051e-01 1.262532e+00
## 1068 4.238298e-01 1.473442e+00 1.397157e+00 1.028268e+00 4.117581e-03
## 1069 4.548958e-01 7.926269e-02 1.954613e-01 2.907154e-02 7.254559e-01
## 1070 3.503558e-01 1.099232e+00 1.020424e-01 3.099253e-02 2.894621e-03
## 1071 7.120345e-01 8.427332e-01 5.976284e-01 3.851204e-01 2.805024e-01
## 1072 2.287300e+00 8.115384e-01 2.363902e-02 1.104417e+00 1.252513e-02
## 1073 4.615958e-01 9.352782e-03 1.384253e-02 5.570136e-01 9.556603e-03
## 1074 2.503702e-01 8.510295e-02 3.685928e-02 1.070631e-01 3.948455e-01
## 1075 1.607746e-02 3.012805e-01 1.089373e-01 1.507252e-01 3.080928e-01
## 1076 6.329666e-03 7.338145e-01 2.209276e-01 2.030125e+00 4.757452e-01
## 1077 1.091471e-01 1.005798e+00 8.358845e-01 6.156461e-01 9.649902e-02
## 1078 2.415940e-01 3.016271e-01 8.820221e-02 4.453588e-01 6.736709e-02
## 1079 3.331795e-01 1.201362e+00 1.978493e-02 1.155161e-02 8.094690e-02
## 1080 1.501533e-01 8.519792e-01 1.139229e-01 7.651004e-03 7.228363e-03
## 1081 3.089531e-03 3.115272e-02 1.316246e-01 1.403750e+00 9.838445e-05
## 1082 1.419293e-01 1.126404e-03 5.236717e-02 1.287731e-01 1.720652e-01
## 1083 1.433445e-03 5.951799e-03 4.792063e-03 1.288993e-01 3.265047e-01
## 1084 3.216551e-04 2.505451e-03 4.196709e-01 2.473597e+00 5.475256e-02
## 1085 2.169732e-01 1.822935e-01 1.421119e+00 3.491276e-02 1.276870e+00
## 1086 1.480108e-01 1.431655e-02 1.350030e-03 2.879891e-01 3.255834e-02
## 1087 4.099265e-02 1.391018e+00 2.408448e-01 2.705000e-01 1.091710e+00
## 1088 2.206509e-04 1.788447e-01 4.329213e-02 2.062971e-01 6.719199e-02
## 1089 2.410133e-01 1.615600e-02 9.614208e-01 3.874332e-02 1.400777e-01
## 1090 3.190172e-02 1.335901e-02 6.306438e-03 1.433058e-02 2.440057e-01
## 1091 5.244155e-01 4.653116e-02 2.556000e-01 9.622791e-02 1.610078e-01
## 1092 5.700328e-02 6.307450e-01 3.657052e-01 1.430206e-01 3.075792e-01
## 1093 6.110614e-01 7.495906e-01 8.605987e-01 2.893628e-02 3.854786e-01
## 1094 4.832511e-02 4.168049e-01 9.797182e-02 4.702038e-03 4.263941e-01
## 1095 4.102899e-01 2.026705e-02 4.681059e-02 2.236079e-01 1.007355e-01
## 1096 7.700642e-01 2.158123e-04 1.009420e-03 7.170258e-02 3.130060e-02
## 1097 4.729764e-02 4.890005e-03 3.172543e-02 1.545841e-01 6.213041e-03
## 1098 7.047008e-03 7.381910e-03 1.447839e-01 1.069510e+00 3.167201e-02
## 1099 2.953948e-02 3.100985e-02 3.137340e-01 1.205484e+00 1.682399e-03
## 1100 4.548958e-01 7.926269e-02 1.954613e-01 2.907154e-02 7.254559e-01
## 1101 2.048942e-01 2.535659e-01 1.565720e-01 1.551499e-01 2.420972e-02
## 1102 5.969754e-01 1.477054e-01 2.455806e-01 4.099386e-03 4.466850e-01
## 1103 1.646836e-01 1.393023e-01 7.069240e-01 3.686347e-01 5.819064e-02
## 1104 5.778224e-02 4.014877e-02 5.288157e-01 3.884280e-01 4.901261e-01
## 1105 3.296257e-01 1.419575e+00 2.520154e-02 1.495759e-02 2.957756e-01
## 1106 7.785858e-02 5.443367e-02 2.082358e-01 1.621046e-04 2.837541e-01
## 1107 2.343675e+00 1.455652e-01 4.409470e-01 3.270550e-02 7.411138e-02
## 1108 4.832511e-02 4.168049e-01 9.797182e-02 4.702038e-03 4.263941e-01
## 1109 6.460784e-01 1.268486e-02 1.642344e+00 2.916420e-01 8.680491e-01
## 1110 1.305518e-01 1.391658e-01 5.324599e-01 1.693666e-01 6.804295e-02
## 1111 6.902729e-02 5.229970e-01 5.158482e-01 8.072369e-02 2.071793e-01
## 1112 3.642015e-01 4.017342e-01 2.569236e-01 4.104865e-05 2.606765e-02
## 1113 2.048942e-01 2.535659e-01 1.565720e-01 1.551499e-01 2.420972e-02
## 1114 6.986347e-02 6.153879e-01 6.333271e-01 7.194934e-01 8.467731e-02
## 1115 7.168891e-01 5.581385e-03 3.065511e-01 8.710130e-02 4.651658e-06
## 1116 5.487263e-01 2.233119e-01 2.602351e-02 3.997233e-02 3.012085e-01
## 1117 7.177011e-03 1.481538e-02 5.574462e-02 6.559896e-01 6.100957e-03
## 1118 3.501986e-01 1.081843e+00 8.540755e-01 2.597799e-01 3.755022e-02
## 1119 2.273216e-01 2.022135e-01 7.691820e-03 1.020865e-02 6.828289e-03
## 1120 1.718896e-06 1.072349e-01 3.989287e-02 6.566037e-01 3.400818e-02
## 1121 5.887576e-03 9.919541e-04 8.689835e-04 7.321203e-03 2.441703e-02
## 1122 7.048647e-03 2.447501e-01 4.804474e-02 2.259168e+00 4.410433e-01
## 1123 4.001221e-01 8.736524e-02 2.422998e-03 1.786109e-01 3.044354e-01
## 1124 2.860629e-01 8.239158e-04 4.044240e-01 5.853207e-03 1.566074e-01
## 1125 8.362198e-03 3.394830e-01 1.361377e-01 5.624003e-01 4.454494e-01
## 1126 1.881969e-04 1.684046e-01 3.874939e-02 1.213578e-01 9.341582e-01
## 1127 4.750512e-01 2.357633e-01 4.057398e-03 2.806601e-01 5.314335e-01
## 1128 1.314834e-02 6.689353e-01 2.353456e-01 1.108875e-01 1.252381e-01
## 1129 7.073151e-02 2.071041e-03 4.073455e-01 1.847656e-01 3.913410e-03
## 1130 2.568445e-02 2.533418e-02 4.780800e-02 1.428851e-02 4.232385e-01
## 1131 5.709067e-01 2.654762e-02 1.485456e+00 1.175461e-02 3.477031e-01
## 1132 2.074136e-01 2.906565e-01 4.850757e-01 3.056486e-03 3.621056e-03
## 1133 2.656332e-01 9.372950e-01 2.555648e+00 1.883173e+00 1.684968e+00
## 1134 4.508072e-01 6.246176e-02 2.188246e-02 2.224943e-02 1.866235e-02
## 1135 4.128976e-01 1.446042e-02 2.280897e-03 2.366232e-01 1.882639e-01
## 1136 4.883118e-02 7.731084e-02 7.823949e-03 1.998124e-01 1.417276e-01
## 1137 8.646616e-02 5.256517e-01 6.411697e-02 3.868034e-04 2.132544e+00
## 1138 6.240450e-02 1.897679e-02 1.208995e-01 8.643908e-03 1.109971e+00
## 1139 2.927513e-02 1.472507e-01 3.190915e-03 7.633623e-01 4.624989e-02
## 1140 1.671054e-01 5.566947e-01 2.075570e-03 4.518110e-02 1.089604e+00
## 1141 5.353075e-01 1.318520e-02 7.317113e-01 6.169573e-03 6.557593e-02
## 1142 3.821961e-02 1.818835e-03 4.166708e-01 4.510746e-04 7.515358e-02
## 1143 1.314834e-02 6.689353e-01 2.353456e-01 1.108875e-01 1.252381e-01
## 1144 2.044879e-01 1.919636e-02 3.800529e-01 5.917429e-01 2.050165e-01
## 1145 4.230493e-01 7.813352e-03 5.538326e-01 1.439503e-03 5.003491e-01
## 1146 5.115071e-01 2.142125e-01 8.859462e-04 7.296383e-02 8.807084e-02
## 1147 1.127041e+00 1.333909e+00 1.076520e-01 5.721119e-02 1.566468e-02
## 1148 2.167347e-01 1.881081e-02 1.743336e-01 1.026198e+00 2.703939e-02
## 1149 1.025082e-02 2.972059e-01 2.332605e-02 9.419208e-02 2.632868e-01
## 1150 5.772896e-03 1.074798e+00 2.985944e+00 4.713878e-01 4.907275e-01
## 1151 7.371058e-01 2.105914e+00 6.431799e-01 1.132041e-01 3.021246e-01
## 1152 9.446868e-02 6.090225e-01 1.337574e-03 5.239488e-01 3.983408e-02
## 1153 5.005803e-01 7.029281e-01 2.996604e-01 3.288738e-01 3.353172e-02
## 1154 8.717853e-02 2.004119e+00 5.702728e-01 8.385790e-01 1.941237e-01
## 1155 4.522992e-04 2.062893e-01 7.626417e-01 1.151617e-01 2.059176e-01
## 1156 3.207196e-02 5.313895e-02 4.372002e-02 4.747957e-04 3.728845e-04
## 1157 2.782463e-01 8.156222e-02 2.614604e-01 8.051254e-01 6.531043e-03
## 1158 3.247691e-02 1.566073e-01 8.762376e-02 3.723670e-02 1.160933e+00
## 1159 3.833252e-01 1.362327e+00 1.717923e+00 2.406256e-01 1.195672e-01
## 1160 3.133134e-02 1.449412e+00 1.420739e-01 4.270487e-02 2.862045e-01
## 1161 3.099060e-02 5.099308e-02 3.012602e-02 4.026679e-02 7.993089e-02
## 1162 1.375281e-01 1.718503e-02 5.118782e-01 9.431351e-01 9.190647e-02
## 1163 1.049415e+00 9.891703e-01 4.778215e-04 4.069002e-02 2.085036e-02
## 1164 1.156190e+00 7.544301e-01 1.435625e+00 5.716007e-01 4.703774e-03
## 1165 1.189438e-01 1.268674e-01 5.255897e-02 8.628441e-04 1.151760e+00
## 1166 1.223481e+00 2.363958e-01 4.916135e-01 2.984842e-02 1.413432e-02
## 1167 6.535339e-01 4.975444e-01 6.765751e-01 8.737618e-02 4.876657e-02
## 1168 3.207196e-02 5.313895e-02 4.372002e-02 4.747957e-04 3.728845e-04
## 1169 9.926153e-01 3.534606e-03 4.137160e-01 1.403071e-01 3.485451e-03
## 1170 1.470828e+00 8.494174e-02 6.722977e-01 7.310998e-01 3.833258e-01
## 1171 1.491045e-01 4.760255e-01 1.202340e+00 2.673166e-05 3.564974e-05
## 1172 4.707830e-01 6.417290e-01 2.375755e-01 4.710559e-01 4.720641e-01
## 1173 4.508072e-01 6.246176e-02 2.188246e-02 2.224943e-02 1.866235e-02
## 1174 2.240103e-01 1.101860e-01 2.245376e-06 1.085028e-01 4.655760e-02
## 1175 3.491345e-01 1.133823e-01 5.377075e-01 5.352517e-02 1.935049e-02
## 1176 1.380965e+00 3.402915e-01 1.190038e+00 6.814597e-03 1.085602e-02
## 1177 5.115071e-01 2.142125e-01 8.859462e-04 7.296383e-02 8.807084e-02
## 1178 4.750488e-02 3.417554e-02 1.218597e-02 8.717329e-02 1.887526e-01
## 1179 1.519849e-01 3.602522e-02 2.177516e-01 1.854230e+00 4.560106e-01
## 1180 4.854909e-01 3.975549e-01 3.612085e-03 8.691214e-02 2.397265e-01
## 1181 2.342343e-02 1.120491e-02 7.316807e-02 3.478161e-01 1.236385e-01
## 1182 1.848991e-01 1.084888e+00 3.853486e-03 1.301774e+00 6.442389e-02
## 1183 1.377572e-01 2.501880e-02 1.125726e-01 7.191164e-01 1.612562e+00
## 1184 2.401307e-01 2.301683e-01 6.715592e-01 1.914983e-03 6.431401e-01
## 1185 8.470537e-02 5.297213e-01 2.074940e-01 9.787360e-02 1.166794e+00
## 1186 1.724247e+00 3.825114e-01 4.799504e-02 3.161124e-01 8.593614e-01
## 1187 4.695772e-01 1.088749e-01 1.222757e+00 2.009341e-01 4.447058e-02
## 1188 1.931793e-02 5.715905e-01 1.144819e-01 6.322264e-01 9.976174e-01
## 1189 4.090707e-01 2.065762e-01 8.214912e-01 5.129864e-01 2.505007e-02
## 1190 3.103967e-01 3.499293e-01 3.239516e-02 2.239666e-01 3.362959e-01
## 1191 1.292562e+00 8.498746e-04 3.610327e-01 4.580092e-01 1.451974e-02
## 1192 2.540061e-02 3.950163e-02 1.003888e-04 3.686651e-01 4.792301e-01
## 1193 9.581563e-02 4.086559e-01 1.616867e-02 5.978624e-02 3.603544e-04
## 1194 9.334412e-05 9.991235e-01 7.193999e-03 7.168514e-01 9.533785e-03
## 1195 1.013376e+00 3.160093e-03 8.762710e-01 1.617932e+00 9.339327e-02
## 1196 2.568445e-02 2.533418e-02 4.780800e-02 1.428851e-02 4.232385e-01
## 1197 1.203827e-01 3.809504e-01 6.646776e-01 2.417638e-02 3.108401e-01
## 1198 2.184212e-03 1.883414e-01 1.592020e-02 3.619210e-02 1.434398e-01
## 1199 1.077818e+00 1.046611e-02 1.171026e-01 9.955443e-02 8.844141e-03
## 1200 2.030983e-01 6.224756e-01 6.525300e-02 2.356379e-02 1.163910e+00
## 1201 6.477824e-02 1.178899e-01 3.359115e-01 1.641897e-01 7.912833e-01
## 1202 1.674428e+00 2.550734e-02 2.722933e-01 6.337718e-02 1.840922e-03
## 1203 9.686528e-01 1.293348e+00 2.110088e-01 1.262311e+00 7.780741e-03
## 1204 8.194494e-01 3.855428e-02 8.246433e-01 3.889400e-01 4.258343e-01
## 1205 3.420246e-02 4.346312e-02 3.278398e-02 1.880437e-02 2.350930e-02
## 1206 1.354381e-01 9.143684e-01 7.557319e-02 2.907766e-01 5.304850e-02
## 1207 3.381608e-02 1.428168e-01 1.776078e-02 9.992988e-01 1.124993e-01
## 1208 4.451917e-01 8.715655e-01 3.356699e-01 7.630903e-02 1.371761e-02
## 1209 1.064387e-02 5.892622e-01 1.725881e-01 5.342887e-01 5.755319e-02
## 1210 1.239890e-03 8.929213e-03 8.558155e-03 8.611782e-01 1.948464e-02
## 1211 3.722614e-01 4.590680e-05 6.024198e-01 7.879347e-01 1.015243e+00
## 1212 9.926153e-01 3.534606e-03 4.137160e-01 1.403071e-01 3.485451e-03
## 1213 6.340874e-01 2.060911e-01 1.018773e-02 1.108767e-01 1.229134e+00
## 1214 3.207639e-01 5.757044e-02 3.721430e-01 3.891594e-01 2.459776e-01
## 1215 1.480108e-01 1.431655e-02 1.350030e-03 2.879891e-01 3.255834e-02
## 1216 6.853350e-03 1.520911e-03 2.276521e-02 3.563552e-01 5.492912e-02
## 1217 2.354321e-04 2.350440e+00 1.618831e-01 4.458911e-02 1.643853e-01
## 1218 2.250769e-03 1.824052e-01 1.585061e+00 1.097596e+00 4.392986e-02
## 1219 5.483163e-01 1.033409e-01 2.149183e-01 1.921508e-01 3.841089e-02
## 1220 3.189503e-01 3.115004e-01 4.216769e-01 2.793209e-02 4.729795e-03
## 1221 6.515851e-03 9.390468e-03 2.833424e+00 8.568292e-05 1.270402e-01
## 1222 1.064814e+00 8.219979e-01 3.721228e-01 3.040439e-01 2.181693e-02
## 1223 1.606718e-01 4.934261e-03 2.103906e-02 4.387919e-01 4.695304e-02
## 1224 1.794297e-01 2.732554e-02 3.839103e-03 6.562744e-01 5.508744e-02
## 1225 7.723067e-02 1.787449e+00 9.861035e-01 5.073569e-03 3.279804e-01
## 1226 3.002904e-01 2.845830e-02 1.914842e-01 4.118823e-01 3.114848e-02
## 1227 1.205337e-01 5.252465e-02 9.750436e-01 5.684343e-01 6.765150e-02
## 1228 9.926153e-01 3.534606e-03 4.137160e-01 1.403071e-01 3.485451e-03
## 1229 6.493218e-01 2.007787e+00 2.204892e-02 3.077021e-02 1.390193e-04
## 1230 1.596251e-02 7.008280e-02 1.974939e-01 3.342813e-02 2.689021e-01
## 1231 1.357886e-01 7.077662e-01 1.849771e-04 4.059698e-01 5.529441e-01
## 1232 1.928131e-04 7.201280e-02 1.111271e-02 1.044200e-01 2.636483e-01
## 1233 1.410649e-03 1.392185e-01 8.906359e-02 2.882073e-01 3.594716e-01
## 1234 2.855540e-01 7.436262e-03 1.207124e-01 4.585733e-04 1.381636e-02
## 1235 7.820546e-03 9.244055e-02 4.825954e-01 9.421127e-01 2.849262e+00
## 1236 2.647271e-01 1.842493e-01 1.551698e-01 7.742786e-02 1.404686e-01
## 1237 1.305823e-02 1.988835e-02 9.607503e-01 9.172639e-02 5.867524e-03
## 1238 9.926153e-01 3.534606e-03 4.137160e-01 1.403071e-01 3.485451e-03
## 1239 1.165691e-01 4.735915e-02 4.288494e-02 3.781084e-04 1.010776e-02
## 1240 5.246627e-01 5.024523e-03 9.242274e-02 1.781068e-01 8.459998e-02
## 1241 3.233108e-02 1.019631e-02 6.191756e-02 4.732419e-01 1.166351e-01
## 1242 2.240103e-01 1.101860e-01 2.245376e-06 1.085028e-01 4.655760e-02
## 1243 5.967122e-01 2.214119e-05 2.439168e-01 4.280370e-02 6.552762e-01
## 1244 2.016134e+00 3.569113e-02 1.694812e-03 1.862205e-01 1.868712e+00
## 1245 6.359081e-02 4.653517e-01 3.071580e-01 1.551267e-03 2.236008e+00
## 1246 1.592614e-01 1.692145e-01 3.756424e-03 1.744201e-01 3.499461e-01
## 1247 1.727273e-01 1.461840e-04 1.072838e-01 7.291148e-03 1.149470e-07
## 1248 7.208575e-02 5.398521e-01 3.860186e-03 2.028436e-01 3.778945e-01
## 1249 8.658112e-03 2.557145e-01 5.105770e-03 4.395589e-01 1.307041e-01
## 1250 4.883118e-02 7.731084e-02 7.823949e-03 1.998124e-01 1.417276e-01
## 1251 4.656942e-01 9.902427e-03 7.165206e-03 1.712458e-01 7.974015e-02
## 1252 2.493298e-01 6.328818e-03 4.739815e-01 6.758457e-02 1.910807e-02
## 1253 2.017763e-01 4.438953e-01 5.027094e-01 7.957053e-01 3.632650e-02
## 1254 2.200467e-02 8.646502e-02 1.231262e-02 1.757064e+00 6.116192e-02
## 1255 2.927513e-02 1.472507e-01 3.190915e-03 7.633623e-01 4.624989e-02
## 1256 9.761638e-02 5.104806e-02 4.287195e-01 5.849637e-01 8.201997e-01
## 1257 6.258040e-01 7.810888e-01 1.429653e-02 2.111741e-01 6.794913e-05
## 1258 1.293829e+00 4.408616e-01 1.834764e+00 7.204003e-02 5.975235e-02
## 1259 1.403017e-04 1.764834e-01 3.324413e-05 1.480714e-02 1.462326e-02
## 1260 3.723526e-02 4.180784e-01 3.010296e-03 4.907062e-07 7.730204e-02
## 1261 7.743823e-05 1.725545e-01 1.508760e-01 3.270866e-03 3.279868e-02
## 1262 3.927088e-01 1.714069e-02 2.871265e-01 8.233334e-01 1.936969e-01
## 1263 3.421858e-01 4.206292e-01 1.164361e-05 7.682044e-01 1.035379e-01
## 1264 5.630513e-01 1.409521e-01 2.469732e-01 5.250831e-03 3.762748e-02
## 1265 7.956277e-03 7.023988e-01 2.645503e-01 2.324304e-01 2.290829e-01
## 1266 3.358796e-02 6.465592e-01 2.439350e-02 5.914010e-01 1.227826e+00
## 1267 3.856760e-02 1.604524e-01 1.908549e-01 4.976937e-01 9.975379e-02
## 1268 6.008417e-02 1.673968e-01 2.216374e-02 3.591602e-01 1.254698e-01
## 1269 6.692538e-02 4.778361e-01 4.592502e-02 1.169865e-01 5.656890e-02
## 1270 1.832927e+00 7.757014e-02 1.040333e-01 1.028195e+00 1.862767e-01
## 1271 1.848991e-01 1.084888e+00 3.853486e-03 1.301774e+00 6.442389e-02
## 1272 2.504492e-01 6.761166e-01 1.078645e-01 1.898425e-04 4.032076e-02
## 1273 5.244155e-01 4.653116e-02 2.556000e-01 9.622791e-02 1.610078e-01
## 1274 1.102095e-01 7.299840e-03 3.803848e-01 4.867713e-01 5.159653e-01
## 1275 3.596327e-01 1.396489e+00 1.045420e-03 3.508788e-01 9.104663e-02
## 1276 6.368597e-01 2.083217e-04 9.168572e-02 4.582472e-01 1.303255e-03
## 1277 9.643710e-02 4.873395e-04 6.235472e-01 3.136584e-01 4.005758e-01
## 1278 7.453825e-01 5.721850e-02 3.685627e-01 3.187699e-01 3.813733e-01
## 1279 3.865308e-01 6.116897e-02 4.468411e-02 1.099238e-01 9.851377e-02
## 1280 2.240103e-01 1.101860e-01 2.245376e-06 1.085028e-01 4.655760e-02
## 1281 3.821961e-02 1.818835e-03 4.166708e-01 4.510746e-04 7.515358e-02
## 1282 5.360050e-01 3.561202e-01 4.489562e-04 4.474473e-03 5.370871e-01
## 1283 1.688004e+00 3.684917e-01 9.433793e-01 1.631584e-02 6.468920e-01
## 1284 6.110614e-01 7.495906e-01 8.605987e-01 2.893628e-02 3.854786e-01
## 1285 1.620043e-01 4.042392e-01 3.058370e-01 8.325433e-02 5.327970e-06
## 1286 6.477824e-02 1.178899e-01 3.359115e-01 1.641897e-01 7.912833e-01
## 1287 6.477824e-02 1.178899e-01 3.359115e-01 1.641897e-01 7.912833e-01
## 1288 3.187974e-01 4.616899e-01 1.666052e-01 7.832630e-02 3.324690e-01
## 1289 5.782800e-02 3.605889e-02 6.591631e-03 1.663269e-05 5.086057e-01
## 1290 1.931793e-02 5.715905e-01 1.144819e-01 6.322264e-01 9.976174e-01
## 1291 7.453825e-01 5.721850e-02 3.685627e-01 3.187699e-01 3.813733e-01
## 1292 4.043112e-03 2.693452e+00 2.006371e-01 7.441243e-01 8.366265e-03
## 1293 4.861190e-01 7.806173e-03 5.252936e-01 9.214106e-01 4.851102e-01
## 1294 5.413404e-02 7.826581e-02 2.234107e-01 1.692994e-01 3.502819e-01
## 1295 3.226913e-04 5.409146e-02 2.055597e-01 5.178427e-03 1.689973e-01
## 1296 3.902515e-02 1.250654e-01 8.933429e-03 8.568317e-01 6.730649e-02
## 1297 7.468878e-01 4.909954e-03 6.657162e-02 2.263257e-01 1.174663e+00
## 1298 1.718896e-06 1.072349e-01 3.989287e-02 6.566037e-01 3.400818e-02
## 1299 1.314834e-02 6.689353e-01 2.353456e-01 1.108875e-01 1.252381e-01
## 1300 3.044125e-01 2.003243e-01 2.879200e-02 1.849950e-01 7.525029e-02
## 1301 1.480108e-01 1.431655e-02 1.350030e-03 2.879891e-01 3.255834e-02
## 1302 4.508072e-01 6.246176e-02 2.188246e-02 2.224943e-02 1.866235e-02
## 1303 3.507889e-02 3.598073e-01 5.292784e-01 1.811353e-02 5.038202e-01
## 1304 4.882578e-02 3.521906e-02 8.447774e-03 1.388579e-03 2.950207e-03
## 1305 2.886269e-03 1.423159e-01 9.410837e-02 3.266623e-02 2.431487e-02
## 1306 4.729764e-02 4.890005e-03 3.172543e-02 1.545841e-01 6.213041e-03
## 1307 7.743823e-05 1.725545e-01 1.508760e-01 3.270866e-03 3.279868e-02
## 1308 1.913254e-02 4.166721e-04 1.240347e-02 5.329083e-01 6.307666e-01
## 1309 3.844612e-03 8.420238e-02 1.809478e+00 5.747547e-02 1.023905e-02
## 1310 1.359888e-01 3.827742e-01 4.074604e-01 1.688238e+00 1.426045e+00
## 1311 7.743823e-05 1.725545e-01 1.508760e-01 3.270866e-03 3.279868e-02
## 1312 5.900150e-01 6.408593e-01 6.250232e-01 3.070506e-01 6.305527e-03
## 1313 3.187974e-01 4.616899e-01 1.666052e-01 7.832630e-02 3.324690e-01
## 1314 4.441726e-01 1.596200e-01 5.771692e-01 1.384139e+00 1.192961e+00
## 1315 6.136969e-02 6.982942e-01 8.718448e-01 8.443613e-03 2.893160e-01
## 1316 6.535339e-01 4.975444e-01 6.765751e-01 8.737618e-02 4.876657e-02
## 1317 3.190172e-02 1.335901e-02 6.306438e-03 1.433058e-02 2.440057e-01
## 1318 6.124199e-02 1.710236e-02 4.656545e-01 7.129110e-03 5.854482e-05
## 1319 3.441128e-01 4.639888e-03 3.913986e-01 4.177974e-01 1.662770e-03
## 1320 3.326288e-01 2.302687e-01 2.655373e-01 1.215971e-01 5.668486e-01
## 1321 8.359772e-02 1.015051e-02 1.102658e-01 1.489100e-01 4.555016e-01
## 1322 3.890847e-03 2.495136e-01 2.918748e-03 1.118625e-03 8.616689e-01
## 1323 3.466124e-01 2.587318e-01 1.116394e-01 3.610756e-02 1.397422e+00
## 1324 3.320074e-01 2.815928e-02 4.684144e-01 2.529883e-03 9.996193e-03
## 1325 1.693392e-06 6.615681e-03 1.599712e-01 1.165738e-01 1.053682e+00
## 1326 2.059691e+00 7.799306e-01 1.520645e+00 1.530612e-01 1.199837e-01
## 1327 7.328256e-03 2.300504e-01 7.547111e-04 6.925440e-03 1.325829e-03
## 1328 4.882578e-02 3.521906e-02 8.447774e-03 1.388579e-03 2.950207e-03
## 1329 1.718896e-06 1.072349e-01 3.989287e-02 6.566037e-01 3.400818e-02
## 1330 1.305518e-01 1.391658e-01 5.324599e-01 1.693666e-01 6.804295e-02
## 1331 5.191097e-02 1.713404e-02 7.227835e-01 4.646677e-02 1.979508e-03
## 1332 2.407477e-01 7.495275e-01 3.106634e-02 1.491504e-02 3.100725e-02
## 1333 2.886269e-03 1.423159e-01 9.410837e-02 3.266623e-02 2.431487e-02
## 1334 8.802847e-01 1.307004e-01 9.018779e-03 1.225310e-01 1.758395e-01
## 1335 2.450511e-01 2.730192e-01 1.506002e-01 1.136547e-02 2.081647e-01
## 1336 1.452170e-02 5.973272e-02 7.864823e-03 1.113668e-01 7.679442e-02
## 1337 1.456826e-01 1.695859e-01 3.061348e-01 4.708031e-02 1.366062e+00
## 1338 9.153805e-02 2.957333e-02 9.350756e-02 6.452434e-02 2.659298e-01
## 1339 8.209171e-03 1.843433e-03 5.223255e-01 2.704720e-01 1.124797e-03
## 1340 9.907570e-04 1.763817e-01 2.331087e+00 3.179481e-02 7.070535e-03
## 1341 1.190616e-01 4.467201e-02 7.672653e-04 6.797430e-03 9.269916e-01
## 1342 1.946797e-01 1.370043e-01 1.089893e+00 8.058604e-02 5.807925e-03
## 1343 1.492185e-02 5.328346e-01 1.061626e-02 1.179650e+00 1.229070e-01
## 1344 4.110874e-02 3.637301e-01 4.286433e-02 1.189176e-02 9.772630e-03
## 1345 3.187974e-01 4.616899e-01 1.666052e-01 7.832630e-02 3.324690e-01
## 1346 1.305823e-02 1.988835e-02 9.607503e-01 9.172639e-02 5.867524e-03
## 1347 1.620164e-02 1.768205e-01 1.068378e-01 6.815351e-02 7.147471e-01
## 1348 2.004656e-01 1.038224e-01 3.594226e-02 6.391148e-01 3.966730e-01
## 1349 4.615958e-01 9.352782e-03 1.384253e-02 5.570136e-01 9.556603e-03
## 1350 1.742217e-02 4.242662e-04 2.980898e-03 2.736510e+00 5.492498e-01
## 1351 3.171656e-01 2.687227e-01 2.046100e-02 4.356909e-01 1.132552e-01
## 1352 6.453124e-02 3.254088e-02 9.524853e-02 6.024314e-01 2.169843e-01
## 1353 5.887576e-03 9.919541e-04 8.689835e-04 7.321203e-03 2.441703e-02
## 1354 4.189540e-01 7.169560e-01 1.510985e-01 1.704647e-01 7.394198e-02
## 1355 3.602984e-01 2.227251e-03 3.400327e-02 1.420115e-01 3.814637e-01
## 1356 9.446868e-02 6.090225e-01 1.337574e-03 5.239488e-01 3.983408e-02
## 1357 6.986347e-02 6.153879e-01 6.333271e-01 7.194934e-01 8.467731e-02
## 1358 4.963778e-01 1.510154e-01 7.273164e-01 4.113304e-03 6.156705e-01
## 1359 4.615958e-01 9.352782e-03 1.384253e-02 5.570136e-01 9.556603e-03
## 1360 6.078234e-01 1.822490e-01 3.920611e-03 5.406753e-03 1.786985e-02
## 1361 1.168695e-01 1.943468e-02 2.487908e+00 3.492311e-02 1.228267e+00
## 1362 2.614175e-02 3.365723e-04 7.742125e-03 2.085932e-01 2.869319e-01
## 1363 1.063956e-01 4.185674e+00 5.714617e-01 3.702658e-02 1.653734e+00
## 1364 1.027515e+00 2.250148e-01 2.166462e-01 5.921124e-03 2.033095e-01
## 1365 5.630229e-01 8.087801e-02 7.524132e-02 7.347516e-02 6.632604e-02
## 1366 4.750488e-02 3.417554e-02 1.218597e-02 8.717329e-02 1.887526e-01
## 1367 1.223481e+00 2.363958e-01 4.916135e-01 2.984842e-02 1.413432e-02
## 1368 3.190172e-02 1.335901e-02 6.306438e-03 1.433058e-02 2.440057e-01
## 1369 1.419293e-01 1.126404e-03 5.236717e-02 1.287731e-01 1.720652e-01
## 1370 1.268218e-01 1.616684e-01 5.540976e-01 4.720088e-01 1.044547e-01
## 1371 3.106681e-02 3.535676e-01 4.220376e-01 2.215926e+00 3.055808e-01
## 1372 9.547333e-01 9.977544e-02 1.395770e-05 3.887594e-01 1.752091e-05
## 1373 9.300926e-03 4.002332e-03 3.596114e-02 4.501769e-01 6.875955e-01
## 1374 1.480108e-01 1.431655e-02 1.350030e-03 2.879891e-01 3.255834e-02
## 1375 1.887273e-01 1.425782e-01 1.004038e-02 3.128854e-03 3.980582e-01
## 1376 4.904233e-02 1.684496e+00 8.190538e-02 4.234314e-02 8.448291e-03
## 1377 4.618680e-02 3.245902e-02 7.413190e-02 2.247967e-01 1.753663e-02
## 1378 6.362997e-03 2.499645e-01 3.142260e-01 5.480384e-02 6.923700e-01
## 1379 2.280075e+00 1.676818e-02 1.040602e-01 2.492335e-02 1.424227e-02
## 1380 1.693392e-06 6.615681e-03 1.599712e-01 1.165738e-01 1.053682e+00
## 1381 2.540061e-02 3.950163e-02 1.003888e-04 3.686651e-01 4.792301e-01
## 1382 5.220145e-02 4.782331e-02 9.997892e-03 2.649284e-02 1.492926e+00
## 1383 5.360050e-01 3.561202e-01 4.489562e-04 4.474473e-03 5.370871e-01
## 1384 5.135155e-02 4.787185e-01 1.318674e-01 2.595241e-01 4.221579e-01
## 1385 4.071197e-02 1.425543e-01 5.463784e-03 5.961388e-02 1.236740e-01
## 1386 3.242142e-01 8.498474e-02 3.999207e-04 9.251340e-02 2.203172e+00
## 1387 2.712403e-01 1.556388e-02 6.162425e-04 1.107395e-01 1.456778e+00# Coordenadas de los puntos de columna
head(ind$coord)## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## 1062 0.3268482 -0.05534045 0.1111824 0.4958503 -0.1595703
## 1063 -0.2937158 -0.36004501 -0.1226376 -0.1079222 -0.1299146
## 1064 0.4195421 -0.33816958 0.3019440 0.2082907 -0.2760005
## 1065 0.7046996 0.05520397 0.1977731 -0.3561133 -0.7981357
## 1066 -0.6871137 0.12469724 1.0579820 -0.6089463 0.3803894
## 1067 -0.1365006 -0.50173787 0.1885246 -0.3523799 -0.8274491# Calidad de la representación
head(ind$cos2)## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## 1062 0.052550247 0.001506496 0.00608071 0.12094382 0.01252525
## 1063 0.057852795 0.086932754 0.01008595 0.00781073 0.01131842
## 1064 0.099423216 0.064596017 0.05149790 0.02450623 0.04302851
## 1065 0.231014375 0.001417658 0.01819557 0.05899395 0.29633604
## 1066 0.156616818 0.005158161 0.37131097 0.12300965 0.04799964
## 1067 0.008441651 0.114054464 0.01610254 0.05625755 0.31019952# Contribuciones
head(ind$contrib)## Dim 1 Dim 2 Dim 3 Dim 4 Dim 5
## 1062 0.1606718 0.004934261 0.02103906 0.43879188 0.04695304
## 1063 0.1297483 0.208857643 0.02559774 0.02078640 0.03112260
## 1064 0.2647271 0.184249305 0.15516985 0.07742786 0.14046862
## 1065 0.7468878 0.004909954 0.06657162 0.22632573 1.17466280
## 1066 0.7100754 0.025052465 1.90507037 0.66178270 0.26681882
## 1067 0.0280231 0.405593088 0.06049094 0.22160508 1.26253173fviz_mca_ind(res.mca, col.ind = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE, # Avoid text overlapping (slow if many points)
ggtheme = theme_minimal())
# Index de la variable de agrupación
fviz_mca_ind(res.mca, habillage = 2, addEllipses = TRUE)
fviz_mca_ind(res.mca,
label = "none",
habillage = "Gender",
pallette = c("#CCCCFF", "#F08080"),
addEllipses = TRUE,
ggtheme = theme_grey())
# Biplot de individuos y categorÃas
fviz_mca_biplot(res.mca, repel = TRUE,
ggtheme = theme_minimal())