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# Version: 03-07-2012, Daniel Fischer
# Changes:
# 03-07-2013: Added the keepPM option
jt.gmw <- function(X,g,goi,type,nper,alternative,mc,PARAMETERS,output, keepPM){
res <- list()
diffTests <- t(as.matrix(sort(goi)))
METHOD <- c("********* Jonckheere-Terpstra Test *********")
DNAME <- PARAMETERS[[1]]
TEST <- PARAMETERS[[2]]
TYPE <- PARAMETERS[[3]]
ALTERNATIVE <- PARAMETERS[[4]]
STATISTIC <- PARAMETERS[[5]]
PVAL <- PARAMETERS[[6]]
dimX <- PARAMETERS[[7]]
XisVector <- PARAMETERS[[8]]
## Case: X is vector
if(XisVector){
##---------------------------------------------------------------------------------------------------------------------------------------
if(alternative=="two.sided"){
if(type=="permutation"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: permutation, two sided, X is vector
for(testRun in 1:nrow(diffTests))
{
obsValue <- jt(X[is.element(g,diffTests[testRun,])],g[is.element(g,diffTests[testRun,])])
nullDist <- jtPTest(X[is.element(g,diffTests[testRun,])],g[is.element(g,diffTests[testRun,])],nper)
PVAL <- 2*min(sum(nullDist>=obsValue)/nper,sum(nullDist<obsValue)/nper)
names(PVAL) <- "p.value"
STATISTIC <- obsValue
names(STATISTIC) <- "obs.value"
ALTERNATIVE <- "two.sided"
resTemp<-c(list(method=METHOD,data.name=DNAME,alternative=ALTERNATIVE,statistic=STATISTIC,test=TEST,p.value=PVAL,type=TYPE))
class(resTemp)<-"htest"
res[[testRun]] <- resTemp
names(res)[testRun] <- paste("H1:",paste(diffTests[testRun,],collapse="<"), "!= ...")
}
if(output=="min")
{
resMin <- matrix(NA,ncol=1,nrow=length(res))
colnames(resMin) <- "pValues"
rownames(resMin) <- names(res)
for(i in 1:length(res))
{
resMin[i,1] <- res[[i]]$p.value
}
res <- resMin
}
} else if(type=="asymptotic"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: asymptotic, two sided, X is vector
res <- c()
stop("We do not have an asymptotic version for the Jonckheere-Terpstra test, sorry!")
} else if(type=="external"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: JT from the clinfun package, two.sided, X is vector
for(testRun in 1:nrow(diffTests))
{ # Our greater and base greater are different interpretations, remeber that!!!
testResult <- jonckheere.test(X[is.element(g,diffTests[testRun,])],g[is.element(g,diffTests[testRun,])] ,alternative="two.sided")
PVAL <- testResult$p.value
names(PVAL) <- "p.value"
STATISTIC <- testResult$statistic
names(STATISTIC) <- "obs.value"
ALTERNATIVE <- "two.sided"
resTemp<-c(list(method=METHOD,data.name=DNAME,alternative=ALTERNATIVE,statistic=STATISTIC,test=TEST,p.value=PVAL,type=TYPE))
class(resTemp)<-"htest"
res[[testRun]] <- resTemp
#names(res)[testRun] <- paste(diffTests[testRun,],collapse="")
names(res)[testRun] <- paste("H1:",paste(diffTests[testRun,],collapse="<"), "!= ...")
}
if(output=="min")
{
resMin <- matrix(NA,ncol=1,nrow=length(res))
colnames(resMin) <- "pValues"
rownames(resMin) <- names(res)
for(i in 1:length(res))
{
resMin[i,1] <- res[[i]]$p.value
}
res <- resMin
}
} else {
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: other options, two sided, X is vector
res <- c()
stop("We do not have this kind of type for the Jonckheere-Terpstra test!\n")
}
##---------------------------------------------------------------------------------------------------------------------------------------
} else if(alternative=="greater"){
if(type=="permutation"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: permutation, greater, X is vector
for(testRun in 1:nrow(diffTests))
{
obsValue <- jt(X[is.element(g,diffTests[testRun,])],g[is.element(g,diffTests[testRun,])])
nullDist <- jtPTest(X[is.element(g,diffTests[testRun,])],g[is.element(g,diffTests[testRun,])],nper)
PVAL <- sum(nullDist>=obsValue)/nper
names(PVAL) <- "p.value"
STATISTIC <- obsValue
names(STATISTIC) <- "obs.value"
ALTERNATIVE <- "greater"
resTemp<-c(list(method=METHOD,data.name=DNAME,alternative=ALTERNATIVE,statistic=STATISTIC,test=TEST,p.value=PVAL,type=TYPE))
class(resTemp)<-"htest"
res[[testRun]] <- resTemp
names(res)[testRun] <- paste("H1:",paste(diffTests[testRun,],collapse="<"), "> ...")
}
if(output=="min")
{
resMin <- matrix(NA,ncol=1,nrow=length(res))
colnames(resMin) <- "pValues"
rownames(resMin) <- names(res)
for(i in 1:length(res))
{
resMin[i,1] <- res[[i]]$p.value
}
res <- resMin
}
} else if(type=="asymptotic"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: asymptotic, greater, X is vector
res <- c()
stop("We do not have an asymptotic version of the Jonckheere-Terpstra test, sorry!\n")
} else if(type=="external"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: JT from the clinfun package, greater, X is vector
for(testRun in 1:nrow(diffTests))
{ # Our greater and base greater are different interpretations, remeber that!!!
testResult <- jonckheere.test(X[is.element(g,diffTests[testRun,])],g[is.element(g,diffTests[testRun,])] ,alternative="increasing")
PVAL <- testResult$p.value
names(PVAL) <- "p.value"
STATISTIC <- testResult$statistic
names(STATISTIC) <- "obs.value"
ALTERNATIVE <- "increasing"
resTemp<-c(list(method=METHOD,data.name=DNAME,alternative=ALTERNATIVE,statistic=STATISTIC,test=TEST,p.value=PVAL,type=TYPE))
class(resTemp)<-"htest"
res[[testRun]] <- resTemp
names(res)[testRun] <- paste("H1:",paste(diffTests[testRun,],collapse="<"), "> ...")
}
if(output=="min")
{
resMin <- matrix(NA,ncol=1,nrow=length(res))
colnames(resMin) <- "pValues"
rownames(resMin) <- names(res)
for(i in 1:length(res))
{
resMin[i,1] <- res[[i]]$p.value
}
res <- resMin
}
} else {
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: other options, greater, X is vector
res <- c()
stop("We do not have this kind of type for the Jonckheere-Terpstra test, sorry!\n")
}
} else if(alternative=="smaller"){
##---------------------------------------------------------------------------------------------------------------------------------------
if(type=="permutation"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: permutation, smaller, X is vector
for(testRun in 1:nrow(diffTests))
{
obsValue <- jt(X[is.element(g,diffTests[testRun,])],g[is.element(g,diffTests[testRun,])])
nullDist <- jtPTest(X[is.element(g,diffTests[testRun,])],g[is.element(g,diffTests[testRun,])],nper)
PVAL <- sum(nullDist<obsValue)/nper
names(PVAL) <- "p.value"
STATISTIC <- obsValue
names(STATISTIC) <- "obs.value"
ALTERNATIVE <- "smaller"
resTemp<-c(list(method=METHOD,data.name=DNAME,alternative=ALTERNATIVE,statistic=STATISTIC,test=TEST,p.value=PVAL,type=TYPE))
class(resTemp)<-"htest"
res[[testRun]] <- resTemp
names(res)[testRun] <- paste("H1:",paste(diffTests[testRun,],collapse="<"), "< ...")
}
if(output=="min")
{
resMin <- matrix(NA,ncol=1,nrow=length(res))
colnames(resMin) <- "pValues"
rownames(resMin) <- names(res)
for(i in 1:length(res))
{
resMin[i,1] <- res[[i]]$p.value
}
res <- resMin
}
} else if(type=="asymptotic"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: asymptotic, smaller, X is vector
res <- c()
stop("We do not have an asymptotic version for the Jonckheere-Terpstra test, sorry!")
} else if(type=="external"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: JT from the clinfun package, smaller, X is vector
for(testRun in 1:nrow(diffTests))
{ # Our greater and base greater are different interpretations, remeber that!!!
testResult <- jonckheere.test(X[is.element(g,diffTests[testRun,])],g[is.element(g,diffTests[testRun,])] ,alternative="decreasing")
PVAL <- testResult$p.value
names(PVAL) <- "p.value"
STATISTIC <- testResult$statistic
names(STATISTIC) <- "obs.value"
ALTERNATIVE <- "increasing"
resTemp<-c(list(method=METHOD,data.name=DNAME,alternative=ALTERNATIVE,statistic=STATISTIC,test=TEST,p.value=PVAL,type=TYPE))
class(resTemp)<-"htest"
res[[testRun]] <- resTemp
names(res)[testRun] <- paste("H1:",paste(diffTests[testRun,],collapse="<"), "< ...")
}
if(output=="min")
{
resMin <- matrix(NA,ncol=1,nrow=length(res))
colnames(resMin) <- "pValues"
rownames(resMin) <- names(res)
for(i in 1:length(res))
{
resMin[i,1] <- res[[i]]$p.value
}
res <- resMin
}
} else {
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: other options, one sided, X is vector
res <- c()
stop("We do not have this kind of type for the Jonckheere-Terpstra test, sorry!")
}
} else {
res <- c()
stop("There is no other option than smaller, greater or two-sided...")
}
## Case: X is a matrix
} else{
##----------------------------------------------------------------------------------------------------------------------------------------
#Preparational things for the case that X is a matrix
# First, restrict the cores to maximum of possible tests
if(mc>detectCores()){
mc <- detectCores()
warning("You do not have so many cores on this machine! I automatically reduced it to your maximum number ",mc)
}
mc <- min(dimX[2],mc)
if(alternative=="two.sided"){
if(type=="permutation"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: permutation, two sided, X is matrix
# Define the function, that is performed for column i (important for parallelization)
innerLoop <- function(i,testRun){
nullDist <- jtPTest(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])],nper)
obsValue <- jt(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])])
pValue <- 2*min(sum(nullDist<obsValue)/nper,sum(nullDist>=obsValue)/nper)
return(list(pValue=pValue,obsValue=obsValue))
}
innerLoopPM <- function(i,testRun){
nullDist <- jtPTest(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])],nper)
obsValue <- jt(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])])
pValue <- 2*min(sum(nullDist<obsValue)/nper,sum(nullDist>=obsValue)/nper)
return(list(pValue=pValue,obsValue=obsValue, nullDist=nullDist))
}
if(keepPM){
nullDistRES <- list()
STATISTIC <- list()
for(i in 1:nrow(diffTests)){
nullDistRES[[i]] <- matrix(0, ncol=dimX[2],nrow=nper)
STATISTIC[[i]] <- c(rep(-1,dimX[2]))
}
}
for(testRun in 1:nrow(diffTests))
{
resTemp <- list()
if(keepPM==TRUE){
resInner <- unlist(mclapply(c(1:dimX[2]),innerLoopPM,testRun=testRun,mc.cores=mc))
#nullDistRES <- matrix(0, ncol=dimX[2],nrow=nper)
} else {
resInner <- unlist(mclapply(c(1:dimX[2]),innerLoop,testRun=testRun,mc.cores=mc))
}
for(i in 1:dimX[2])
{
if(keepPM==TRUE){
PVAL <- resInner[nper*(i-1) + 2*(i) - 1]
STATISTIC[[testRun]][i] <- resInner[nper*(i-1) + 2*i]
nullDistRES[[testRun]][,i] <- resInner[(nper*(i-1) + 2*i + 1):(nper*i + 2*i)]
} else {
PVAL <- resInner[2*i-1]
STATISTIC <- resInner[2*i]
}
obsValue <- STATISTIC
names(PVAL) <- "p.value"
ALTERNATIVE <- "two.sided"
names(STATISTIC) <- "obs.value"
resTemp[[i]]<-c(list(method=METHOD,data.name=DNAME,alternative=ALTERNATIVE,statistic=STATISTIC,test=TEST,p.value=PVAL,type=TYPE))
class(resTemp[[i]])<-"htest"
}
res[[testRun]] <- resTemp
names(res)[testRun] <- paste("H1:",paste(diffTests[testRun,],collapse="<"), "!= ...")
}
if(output=="min")
{
resMin <- matrix(NA,ncol=dimX[2],nrow=length(res))
colnames(resMin) <- colnames(X)
rownames(resMin) <- names(res)
for(i in 1:length(res))
{
for(j in 1:dimX[2])
{
resMin[i,j] <- res[[i]][[j]]$p.value
}
}
res <- resMin
}
} else if(type=="asymptotic"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: asymptotic, two sided, X is matrix
res <- c()
stop("We do not have an asymptotic version for the Jonckheere-Terpstra test, sorry!")
} else if(type=="external"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: base, two sided, X is matrix
innerLoop <- function(i,testRun){
testResult <- jonckheere.test(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])] ,alternative="two.sided")
obsValue <- testResult$statistic
pValue <- testResult$p.value
return(list(pValue=pValue,obsValue=obsValue))
}
for(testRun in 1:nrow(diffTests))
{
resTemp <- list()
resInner <- unlist(mclapply(c(1:dimX[2]),innerLoop,testRun=testRun,mc.cores=mc))
for(i in 1:dimX[2])
{
PVAL <- resInner[2*i-1]
STATISTIC <- resInner[2*i]
names(PVAL) <- "p.value"
ALTERNATIVE <- "two.sided"
names(STATISTIC) <- "obs.value"
resTemp[[i]]<-c(list(method=METHOD,data.name=DNAME,alternative=ALTERNATIVE,statistic=STATISTIC,test=TEST,p.value=PVAL,type=TYPE))
class(resTemp[[i]])<-"htest"
}
res[[testRun]] <- resTemp
names(res)[testRun] <- paste("H1:",paste(diffTests[testRun,],collapse="<"), "!= ...")
}
if(output=="min")
{
resMin <- matrix(NA,ncol=dimX[2],nrow=length(res))
colnames(resMin) <- colnames(X)
rownames(resMin) <- names(res)
for(i in 1:length(res))
{
for(j in 1:dimX[2])
{
resMin[i,j] <- res[[i]][[j]]$p.value
}
}
res <- resMin
}
} else {
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: other options, two sided, X is matrix
res <- c()
stop("We do not have this kind of type for the Jonckheere-Terpstra test!")
}
} else if(alternative=="greater"){
if(type=="permutation"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: permutation, greater, X is matrix
# Define the function, that is performed for column i (important for parallelization)
innerLoop <- function(i,testRun){
nullDist <- jtPTest(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])],nper)
obsValue <- jt(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])])
pValue <- sum(nullDist>=obsValue)/nper
return(list(pValue=pValue,obsValue=obsValue))
}
innerLoopPM <- function(i,testRun){
nullDist <- jtPTest(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])],nper)
obsValue <- jt(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])])
pValue <- sum(nullDist>=obsValue)/nper
return(list(pValue=pValue,obsValue=obsValue, nullDist=nullDist))
}
if(keepPM){
nullDistRES <- list()
STATISTIC <- list()
for(i in 1:nrow(diffTests)){
nullDistRES[[i]] <- matrix(0, ncol=dimX[2],nrow=nper)
STATISTIC[[i]] <- c(rep(-1,dimX[2]))
}
}
for(testRun in 1:nrow(diffTests))
{
resTemp <- list()
if(keepPM==TRUE){
resInner <- unlist(mclapply(c(1:dimX[2]),innerLoopPM,testRun=testRun,mc.cores=mc))
#nullDistRES <- matrix(0, ncol=dimX[2],nrow=nper)
} else {
resInner <- unlist(mclapply(c(1:dimX[2]),innerLoop,testRun=testRun,mc.cores=mc))
}
for(i in 1:dimX[2])
{
if(keepPM==TRUE){
PVAL <- resInner[nper*(i-1) + 2*(i) - 1]
STATISTIC[[testRun]][i] <- resInner[nper*(i-1) + 2*i]
nullDistRES[[testRun]][,i] <- resInner[(nper*(i-1) + 2*i + 1):(nper*i + 2*i)]
} else {
PVAL <- resInner[2*i-1]
STATISTIC <- resInner[2*i]
}
obsValue <- STATISTIC
names(PVAL) <- "p.value"
ALTERNATIVE <- "greater"
names(STATISTIC) <- "obs.value"
resTemp[[i]]<-c(list(method=METHOD,data.name=DNAME,alternative=ALTERNATIVE,statistic=STATISTIC,test=TEST,p.value=PVAL,type=TYPE))
class(resTemp[[i]])<-"htest"
}
res[[testRun]] <- resTemp
names(res)[testRun] <- paste("H1:",paste(diffTests[testRun,],collapse="<"), "> ...")
}
if(output=="min")
{
resMin <- matrix(NA,ncol=dimX[2],nrow=length(res))
colnames(resMin) <- colnames(X)
rownames(resMin) <- names(res)
for(i in 1:length(res))
{
for(j in 1:dimX[2])
{
resMin[i,j] <- res[[i]][[j]]$p.value
}
}
res <- resMin
}
} else if(type=="asymptotic"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: asymptotic, greater, X is matrix
res <- c()
stop("We do not have an asymptotic version for the Jonckheere-Terpstra test, sorry!")
} else if(type=="external"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: base, greater, X is matrix
innerLoop <- function(i,testRun){
testResult <- jonckheere.test(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])] ,alternative="increasing")
obsValue <- testResult$statistic
pValue <- testResult$p.value
return(list(pValue=pValue,obsValue=obsValue))
}
for(testRun in 1:nrow(diffTests))
{
resTemp <- list()
resInner <- unlist(mclapply(c(1:dimX[2]),innerLoop,testRun=testRun,mc.cores=mc))
for(i in 1:dimX[2])
{
PVAL <- resInner[2*i-1]
STATISTIC <- resInner[2*i]
names(PVAL) <- "p.value"
ALTERNATIVE <- "greater"
names(STATISTIC) <- "obs.value"
resTemp[[i]]<-c(list(method=METHOD,data.name=DNAME,alternative=ALTERNATIVE,statistic=STATISTIC,test=TEST,p.value=PVAL,type=TYPE))
class(resTemp[[i]])<-"htest"
}
res[[testRun]] <- resTemp
names(res)[testRun] <- paste("H1:",paste(diffTests[testRun,],collapse="<"), "> ...")
}
if(output=="min")
{
resMin <- matrix(NA,ncol=dimX[2],nrow=length(res))
colnames(resMin) <- colnames(X)
rownames(resMin) <- names(res)
for(i in 1:length(res))
{
for(j in 1:dimX[2])
{
resMin[i,j] <- res[[i]][[j]]$p.value
}
}
res <- resMin
}
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: other, greater, X is matrix
} else {
res <- c()
stop("We do not have this kind of type for the Jonckheere-Terpstra test, sorry!")
}
} else if(alternative=="smaller"){
if(type=="permutation"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: permutation, smaller, X is matrix
# Define the function, that is performed for column i (important for parallelization)
innerLoop <- function(i,testRun){
nullDist <- jtPTest(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])],nper)
obsValue <- jt(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])])
pValue <- sum(nullDist<obsValue)/nper
return(list(pValue=pValue,obsValue=obsValue))
}
innerLoopPM <- function(i,testRun){
nullDist <- jtPTest(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])],nper)
obsValue <- jt(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])])
pValue <- sum(nullDist<obsValue)/nper
return(list(pValue=pValue,obsValue=obsValue, nullDist=nullDist))
}
if(keepPM){
nullDistRES <- list()
STATISTIC <- list()
for(i in 1:nrow(diffTests)){
nullDistRES[[i]] <- matrix(0, ncol=dimX[2],nrow=nper)
STATISTIC[[i]] <- c(rep(-1,dimX[2]))
}
}
for(testRun in 1:nrow(diffTests))
{
resTemp <- list()
if(keepPM==TRUE){
resInner <- unlist(mclapply(c(1:dimX[2]),innerLoopPM,testRun=testRun,mc.cores=mc))
#nullDistRES <- matrix(0, ncol=dimX[2],nrow=nper)
} else {
resInner <- unlist(mclapply(c(1:dimX[2]),innerLoop,testRun=testRun,mc.cores=mc))
}
for(i in 1:dimX[2])
{
if(keepPM==TRUE){
PVAL <- resInner[nper*(i-1) + 2*(i) - 1]
STATISTIC[[testRun]][i] <- resInner[nper*(i-1) + 2*i]
nullDistRES[[testRun]][,i] <- resInner[(nper*(i-1) + 2*i + 1):(nper*i + 2*i)]
} else {
PVAL <- resInner[2*i-1]
STATISTIC <- resInner[2*i]
}
obsValue <- STATISTIC
names(PVAL) <- "p.value"
ALTERNATIVE <- "smaller"
names(STATISTIC) <- "obs.value"
resTemp[[i]]<-c(list(method=METHOD,data.name=DNAME,alternative=ALTERNATIVE,statistic=STATISTIC,test=TEST,p.value=PVAL,type=TYPE))
class(resTemp[[i]])<-"htest"
}
res[[testRun]] <- resTemp
names(res)[testRun] <- paste("H1:",paste(diffTests[testRun,],collapse="<"), "< ...")
}
if(output=="min")
{
resMin <- matrix(NA,ncol=dimX[2],nrow=length(res))
colnames(resMin) <- colnames(X)
rownames(resMin) <- names(res)
for(i in 1:length(res))
{
for(j in 1:dimX[2])
{
resMin[i,j] <- res[[i]][[j]]$p.value
}
}
res <- resMin
}
} else if(type=="asymptotic"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: asymptotic, smaller, X is matrix
res <- c()
warning("We do not have an asymptotic version for the Jonckheere-Terpstra test, sorry!")
} else if(type=="external"){
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: base, smaller, X is matrix
innerLoop <- function(i,testRun){
testResult <- jonckheere.test(X[is.element(g,diffTests[testRun,]),i],g[is.element(g,diffTests[testRun,])] ,alternative="decreasing")
obsValue <- testResult$statistic
pValue <- testResult$p.value
return(list(pValue=pValue,obsValue=obsValue))
}
for(testRun in 1:nrow(diffTests))
{
resTemp <- list()
resInner <- unlist(mclapply(c(1:dimX[2]),innerLoop,testRun=testRun,mc.cores=mc))
for(i in 1:dimX[2])
{
PVAL <- resInner[2*i-1]
STATISTIC <- resInner[2*i]
names(PVAL) <- "p.value"
ALTERNATIVE <- "smaller"
names(STATISTIC) <- "obs.value"
resTemp[[i]]<-c(list(method=METHOD,data.name=DNAME,alternative=ALTERNATIVE,statistic=STATISTIC,test=TEST,p.value=PVAL,type=TYPE))
class(resTemp[[i]])<-"htest"
}
res[[testRun]] <- resTemp
names(res)[testRun] <- paste("H1:",paste(diffTests[testRun,],collapse="<"), "< ...")
}
if(output=="min")
{
resMin <- matrix(NA,ncol=dimX[2],nrow=length(res))
colnames(resMin) <- colnames(X)
rownames(resMin) <- names(res)
for(i in 1:length(res))
{
for(j in 1:dimX[2])
{
resMin[i,j] <- res[[i]][[j]]$p.value
}
}
res <- resMin
}
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: other, smaller, X is matrix
} else {
res <- c()
stop("We do not have this kind of type for the Jonckheere-Terpstra test, sorry!")
}
#----------------------------------------------------------------------------------------------------------------------------------------
# Case: other, other, X is matrix
} else {
res <- c()
stop("There are no other alternatives possible, sorry!")
}
}
if(type=="permutation"){
ifelse(keepPM,res <- list(p.values=res, nullDist=nullDistRES, obsValue=obsValue), res <- list(p.values=res))
} else {
res <- list(p.values=res)
}
res
}
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