Nothing
pp.kSamples <- function(x){
if(!inherits(x,"kSamples", TRUE)) stop('input not of class "kSamples"\n')
if(x$test.name == "Anderson-Darling"){
if(is.null(x$null.dist1)) stop("the null.dist1 & null.dist2 components of input are NULL\n")
}else{
if(is.null(x$null.dist)) stop("the null.dist component of input is NULL\n")
}
if(x$test.name == "Anderson-Darling"){
version <- "0"
while(substr(version,1,1) != "1" & substr(version,1,1) != "2"){
version <- readline("choose version of test statistic: 1 or 2\n")
}
if(names(x)[[2]]=="k") {
dist <- x[[8+as.numeric(version)]]}else{
dist <- x[[12+as.numeric(version)]]
}
if(!is.null(dist)){
xy <- table(dist)
N <- length(dist)
if(names(x)[[2]]=="k") {
xx <- (as.numeric(names(xy))-(x$k-1))/x$sig
px <- ad.pval(xx,x$k-1,as.numeric(version))}else{
xx <- (as.numeric(names(xy))-(x$mu.c))/x$sig.c
px <- ad.pval(xx,x$mu.c,as.numeric(version))
}
px.exact <- rev(cumsum(rev(as.numeric(xy)))/N)
m <- min(px,px.exact)
M <- max(px,px.exact)
par(pty="s")
if(names(x)[[2]]=="k") titlex <- paste(x$test.name,"k-sample test, version", version)
if(names(x)[[2]]=="M") titlex <- paste("combined", x$test.name,"k-sample tests, version", version)
plot(px.exact,px,log="xy",xlim=c(m,M), ylim=c(m,M), main= titlex,
xlab=paste(x$method,"significance probability"),ylab="asymptotic significance probability",pch=16,cex=.5)
text(.055,m,".05",adj=0)
abline(0,1,lty=2)
abline(h=.05,lty=2)
abline(v=.05,lty=2)
text(.012,.5,".01",adj=0)
abline(h=.01,lty=2)
abline(v=.01,lty=2)
if(x$method=="simulated"){
text(m,M,paste("Nsim =",x$Nsim),adj=0)}else{
text(m,M,paste("Ncomb =",length(dist)),adj=0)
}
}else{
cat("no distribution data\n")
}
}
if(x$test.name == "Kruskal-Wallis" |
x$test.name == "van der Waerden scores" |
x$test.name == "normal scores"){
dist <- x$null.dist
if(!is.null(dist)){
xy <- table(dist)
N <- length(dist)
xx <- as.numeric(names(xy))
if(names(x)[[2]] == "k"){
px <- 1-pchisq(xx,x$k - 1)}else{
df <- sum(sapply(x$n.samples,length))-length(x$n.samples)
px <- 1-pchisq(xx,df)
}
px.exact <- rev(cumsum(rev(as.numeric(xy)))/N)
m <- min(px,px.exact)
M <- max(px,px.exact)
par(pty="s")
if(names(x)[[2]]=="k") titlex <- paste(x$test.name,"k-sample test")
if(names(x)[[2]]=="M") titlex <- paste("combined", x$test.name,"k-sample tests")
plot(px.exact,px,log="xy",xlim=c(m,M), ylim=c(m,M), main= titlex,
xlab=paste(x$method,"significance probability"),
ylab="asymptotic significance probability",pch=16,cex=.5)
text(.055,m,".05",adj=0)
abline(0,1,lty=2)
abline(h=.05,lty=2)
abline(v=.05,lty=2)
text(.012,.5,".01",adj=0)
abline(h=.01,lty=2)
abline(v=.01,lty=2)
if(x$method=="simulated"){
text(m,M,paste("Nsim =",x$Nsim),adj=0)}else{
text(m,M,paste("Ncomb =",length(dist)),adj=0)
}
}else{
cat("no distribution data\n")
}
}
if(x$test.name == "Jonckheere-Terpstra"){
dist <- x$null.dist
if(!is.null(dist)){
xy <- table(dist)
N <- length(dist)
xx <- as.numeric(names(xy))
mu <- x$JT[2]
sig <- x$JT[3]
px <- 1-pnorm(xx,mu,sig)
px.exact <- rev(cumsum(rev(as.numeric(xy)))/N)
m <- min(px,px.exact)
M <- max(px,px.exact)
par(pty="s")
titlex <- paste(x$test.name,"k-sample test")
plot(px.exact,px,log="xy",xlim=c(m,M),
ylim=c(m,M), main= titlex,
xlab=paste(x$method,"significance probability"),
ylab="asymptotic significance probability",pch=16,cex=.5)
text(.055,m,".05",adj=0)
abline(0,1,lty=2)
abline(h=.05,lty=2)
abline(v=.05,lty=2)
text(.012,.5,".01",adj=0)
abline(h=.01,lty=2)
abline(v=.01,lty=2)
if(x$method=="simulated"){
text(m,M,paste("Nsim =",x$Nsim),adj=0)}else{
text(m,M,paste("Ncomb =",length(dist)),adj=0)
}
}else{
cat("no distribution data\n")
}
}
if(x$test.name == "2 x t Contingency Table" |
x$test.name == "Combined 2 x t Contingency Tables"){
dist <- x$null.dist
if(!is.null(dist)){
xx <- dist[,1]
px.exact <- rev(cumsum(rev(dist[,2])))
N <- length(dist[,1])
if(names(x)[[3]] == "M"){
M <- x$M
tvec <- x$t
df <- sum(tvec)-M
}else{
df <- x$t -1
}
px <- pchisq(xx,df,lower.tail=FALSE)
m <- min(px,px.exact)
M <- max(px,px.exact)
plot(px.exact,px,log="xy",xlim=c(m,M), ylim=c(m,M), main= x$test.name,
xlab=paste(x$method,"significance probability"),ylab="asymptotic significance probability",pch=16,cex=.5)
text(.055,m,".05",adj=0)
abline(0,1,lty=2)
abline(h=.05,lty=2)
abline(v=.05,lty=2)
text(.008,.5,".01",adj=1)
abline(h=.01,lty=2)
abline(v=.01,lty=2)
if(x$method=="simulated"){
text(m,M,paste("Nsim =",x$Nsim),adj=0)}else{
text(m,M,paste("Nsupp =",length(dist[,1])),adj=0)
}
}else{
cat("no distribution data\n")
}
}
if(x$test.name == "Steel"){
dist <- x$null.dist
if(!is.null(dist)){
xy <- table(dist)
N <- length(dist)
xx <- as.numeric(names(xy))
tau <- x$tau
sig <- x$sig
sig0 <- x$sig0
ni <- x$ns[-1]
px <- Steelnormal0(sig0,sig,tau,xx,ni, alternative= x$alternative)
px.exact <- rev(cumsum(rev(as.numeric(xy)))/N)
m <- min(px,px.exact)
M <- max(px,px.exact)
par(pty="s")
titlex <- paste(x$test.name,"k-sample test")
plot(px.exact,px,log="xy",xlim=c(m,M),
ylim=c(m,M), main= titlex,
xlab=paste(x$method,"significance probability"),
ylab="asymptotic significance probability",pch=16,cex=.5)
text(.055,m,".05",adj=0)
abline(0,1,lty=2)
abline(h=.05,lty=2)
abline(v=.05,lty=2)
text(.012,.5,".01",adj=0)
abline(h=.01,lty=2)
abline(v=.01,lty=2)
if(x$method=="simulated"){
text(m,M,paste("Nsim =",x$Nsim),adj=0)}else{
text(m,M,paste("Ncomb =",length(dist)),adj=0)
}
}else{
cat("no distribution data\n")
}
}
}
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