Nothing
################################################################################
# summary.ca(): Summarizing ca objects (ca package 0.70)
################################################################################
summary.ca <- function(object, scree = TRUE, rows = TRUE, columns = TRUE, ...){
obj <- object
nd <- obj$nd
if (is.na(nd)){
nd <- 2
} else {
if (nd > length(obj$sv)){
nd <- length(obj$sv)
}
}
# principal coordinates:
K <- nd
I <- dim(obj$rowcoord)[1] ; J <- dim(obj$colcoord)[1]
svF <- matrix(rep(obj$sv[1:K], I), I, K, byrow = TRUE)
svG <- matrix(rep(obj$sv[1:K], J), J, K, byrow = TRUE)
rpc <- obj$rowcoord[,1:K] * svF
cpc <- obj$colcoord[,1:K] * svG
# rows:
strnascii <- function(x){
foo1 <- unlist(strsplit(x, ""))
foo2 <- grep('\\w', foo1)
foo <- paste(foo1[foo2], collapse = "")
return(foo)
}
if(!rows) {
r.out <- NULL
} else {
rnames.temp <- unlist(lapply(obj$rownames, strnascii))
r.names <- abbreviate(rnames.temp, 4)
sr <- obj$rowsup
if (!is.na(sr[1])){
r.names[sr] <- paste("(*)", r.names[sr], sep = "")
}
r.mass <- obj$rowmass
if (length(obj$rowsup)>0){
i0 <- obj$rowsup
r.mass[i0] <- NA
}
r.inr <- obj$rowinertia / sum(obj$rowinertia, na.rm = TRUE)
r.ccc <- matrix(NA, nrow = length(r.names), ncol = nd * 3)
for (i in 1:nd){
r.ccc[,3 * (i - 1) + 1] <- rpc[,i]
# r.ccc[,3 * (i - 1) + 2] <- rpc[,i]^2 / obj$rowdist^2
rpc0 <- cacoord(obj, type = "principal", rows = TRUE)
r.ccc[,3 * (i - 1) + 2] <- rpc0[,i]^2 / apply(rpc0^2, 1, sum)
r.ccc[,3 * (i - 1) + 3] <- obj$rowmass * rpc[,i]^2 /obj$sv[i]^2
}
if (nd > 1) {
r.qlt <- apply(r.ccc[,((1:nd-1) * 3 + 2)], 1, sum) }
else {
r.qlt <- r.ccc[,((1:nd-1) * 3 + 2)]
}
r1 <- paste(" k=", 1:nd, sep = "")
r2 <- rep("cor", nd)
r3 <- rep("ctr", nd)
rcclab <- as.vector(rbind(r1, r2, r3))
dimnames(r.ccc) <- list(r.names, rcclab)
r.out <- data.frame(r.names, round(1000 * r.mass, 0), round(1000 * r.qlt, 0),
round(1000 * r.inr, 0), round(1000 * r.ccc, 0))
dimnames(r.out) <- list(as.character(1:length(r.names)), c("name", "mass", " qlt", " inr", rcclab))
}
# columns:
if(!columns) {
c.out <- NULL
} else {
cnames.temp <- unlist(lapply(obj$colnames, strnascii))
c.names <- abbreviate(cnames.temp, 4)
sc <- obj$colsup
if (!is.na(sc[1])){
c.names[sc] <- paste("(*)", c.names[sc], sep = "")
}
c.mass <- obj$colmass
if (length(obj$colsup) > 0){
i0 <- obj$colsup
c.mass[i0] <- NA
}
c.inr <- obj$colinertia / sum(obj$colinertia, na.rm = TRUE)
c.ccc <- matrix(NA, nrow = length(c.names), ncol = nd * 3)
for (i in 1:nd){
c.ccc[,3 * (i - 1) + 1] <- cpc[,i]
# c.ccc[,3 * (i - 1) + 2] <- cpc[,i]^2 / obj$coldist^2
cpc0 <- cacoord(obj, type = "principal", cols = TRUE)
c.ccc[,3 * (i - 1) + 2] <- cpc0[,i]^2 / apply(cpc0^2, 1, sum)
c.ccc[,3 * (i - 1) + 3] <- obj$colmass * cpc[,i]^2 / obj$sv[i]^2
}
if (nd > 1) {
c.qlt <- apply(c.ccc[,((1:nd - 1) * 3 + 2)], 1, sum) }
else {
c.qlt <- c.ccc[,((1:nd - 1) * 3 + 2)]
}
c1 <- paste(" k=", 1:nd, sep = "")
c2 <- rep("cor", nd)
c3 <- rep("ctr", nd)
ccclab <- as.vector(rbind(c1, c2, c3))
dimnames(c.ccc) <- list(c.names, ccclab)
c.out <- data.frame(c.names, round(1000 * c.mass, 0), round(1000 * c.qlt, 0),
round(1000 * c.inr, 0), round(1000 * c.ccc, 0))
dimnames(c.out) <- list(as.character(1:length(c.names)), c("name", "mass", " qlt", " inr", ccclab))
}
# scree plot:
if (scree) {
values <- obj$sv^2
values2 <- 100*(obj$sv^2)/sum(obj$sv^2)
values3 <- cumsum(100*(obj$sv^2)/sum(obj$sv^2))
scree.out <- cbind(1:length(obj$sv), values, values2, values3)
} else {
scree.out <- NULL
}
# output:
out <- list(scree = scree.out,
rows = r.out,
columns = c.out)
class(out) <- "summary.ca"
return(out)
}
################################################################################
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