summary.PCA.Bootstrap <- function(object, ...){
cat(" ###### Bootstrap for Principal Components Analysis #######\n\n")
rnames=rownames(object$InitialData)
cnames=colnames(object$InitialData)
cat("Transformation of the raw data:\n")
print(object$InitTransform)
cat("\n\nEigenvalues\n")
MedEig=apply(object$EigVal^2, 2,mean)
ICPerc=apply(object$EigVal^2, 2,quantile, c(0.025, 0.975))
sdev=apply(object$EigVal^2, 2,sd)
m1=cbind(round(object$InitialSVD$d^2,3), round(MedEig, 3), round(t(ICPerc), 3), round(MedEig-1.96*sdev, 3), round(MedEig+1.96*sdev, 3))
rownames(m1)=paste("Dim", 1:length(MedEig))
colnames(m1)=c("Initial", "Bootstrap Mean", "CI- P2.5", "CI- P97.5", "CI- M EI", "CI- M ES")
print(m1)
cat("\n\nAccounted Variance\n")
MedEig=apply(object$Inertia, 2,mean)
ICPerc=apply(object$Inertia, 2,quantile, c(0.025, 0.975))
sdev=apply(object$Inertia, 2,sd)
Inertia=100*object$InitialSVD$d^2/sum(object$InitialSVD$d^2)
m1=cbind(round(Inertia,3), round(MedEig, 3), round(t(ICPerc), 3), round(MedEig-1.96*sdev, 3), round(MedEig+1.96*sdev, 3))
rownames(m1)=paste("Dim", 1:length(MedEig))
colnames(m1)=c("Initial", "Bootstrap Mean", "CI- P2.5", "CI- P97.5", "CI- M EI", "CI- M ES")
print(m1)
cat("\n\nEigenvector Coefficients\n")
dimens=dim(object$InitialSVD$u)[2]
for (i in 1:dimens){
cat("\nPrincipal Component :",i,"\n")
bb=t(as.matrix(object$Vs[,i,]))
media=apply(bb, 2,mean)
ICPerc=apply(bb, 2,quantile, c(0.025, 0.975))
sdev=apply(bb, 2,sd)
m1=cbind(round(object$InitialSVD$v[,i],3), round(media, 3), round(t(ICPerc), 3), round(media-1.96*sdev, 3), round(media+1.96*sdev, 3))
colnames(m1)=c("Initial", "Bootstrap Mean", "CI- P2.5", "CI- P97.5", "CI- M EI", "CI- M ES")
print(m1)
}
cat("\n\nCorrelations with the components\n")
for (i in 1:dimens){
cat("\nPrincipal Component :",i,"\n")
bb=t(as.matrix(object$Struct[,i,]))
media=apply(bb, 2,mean)
ICPerc=apply(bb, 2,quantile, c(0.025, 0.975))
sdev=apply(bb, 2,sd)
m1=cbind(round(object$InitCorr[,i],3), round(media, 3), round(t(ICPerc), 3), round(media-1.96*sdev, 3), round(media+1.96*sdev, 3))
colnames(m1)=c("Initial", "Bootstrap Mean", "CI- P2.5", "CI- P97.5", "CI- M EI", "CI- M ES")
print(m1)
}
cat("\n\nSquared Correlations with the components\n")
for (i in 1:dimens){
cat("\nPrincipal Component :",i,"\n")
bb=t(as.matrix(object$Struct[,i,]^2))
media=apply(bb, 2,mean)
ICPerc=apply(bb, 2,quantile, c(0.025, 0.975))
m1=cbind(round(object$InitCorr[,i]^2,3), round(media, 3), round(t(ICPerc), 3))
colnames(m1)=c("Initial", "Bootstrap Mean", "CI- P2.5", "CI- P97.5")
print(m1)
}
cat("\n\nRow Scores\n")
for (i in 1:dimens){
cat("\nPrincipal Component :",i,"\n")
bb=t(as.matrix(object$Scores[,i,]))
media=apply(bb, 2,mean)
ICPerc=apply(bb, 2,quantile, c(0.025, 0.975))
sdev=apply(bb, 2,sd)
m1=cbind(round(object$InitScores[,i],3), round(media, 3), round(t(ICPerc), 3), round(media-1.96*sdev, 3), round(media+1.96*sdev, 3))
colnames(m1)=c("Initial", "Bootstrap Mean", "CI- P2.5", "CI- P97.5", "CI- M EI", "CI- M ES")
print(m1)
}
}
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