Nothing
pball <- function(x, beta = 0.2, ...){
#
# Compute the percentage bend correlation matrix for the
# data in the n by p matrix m.
#
# This function also returns the two-sided significance level
# for all pairs of variables, plus a test of zero correlations
# among all pairs. (See chapter 6 for details.)
#
cl <- match.call()
m <- x
pbcorm<-matrix(0,ncol(m),ncol(m))
temp<-matrix(1,ncol(m),ncol(m))
siglevel<-matrix(NA,ncol(m),ncol(m))
cmat<-matrix(0,ncol(m),ncol(m))
for (i in 1:ncol(m)){
ip1<-i
for (j in ip1:ncol(m)){
if(i<j){
pbc<-pbcor(m[,i],m[,j],beta)
pbcorm[i,j]<-pbc$cor
temp[i,j]<-pbcorm[i,j]
temp[j,i]<-pbcorm[i,j]
siglevel[i,j]<-pbc$p.value
siglevel[j,i]<-siglevel[i,j]
}
}
}
tstat<-pbcorm*sqrt((nrow(m)-2)/(1-pbcorm^2))
cmat<-sqrt((nrow(m)-2.5)*log(1+tstat^2/(nrow(m)-2)))
bv<-48*(nrow(m)-2.5)^2
cmat<-cmat+(cmat^3+3*cmat)/bv-(4*cmat^7+33*cmat^5+240^cmat^3+855*cmat)/(10*bv^2+8*bv*cmat^4+1000*bv)
H<-sum(cmat^2)
df<-ncol(m)*(ncol(m)-1)/2
h.siglevel<-1-pchisq(H,df)
if (!is.null(colnames(x))) rownames(temp) <- colnames(temp) <- rownames(siglevel) <- colnames(siglevel) <- colnames(x)
result <- list(pbcorm = temp, p.values = siglevel, H = H, H.p.value = h.siglevel, call = cl)
class(result) <- "pball"
result
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.