R/TWOpovPV.R

In musto101/wilcox_R: What the package does (short line)

TWOpovPV <-
function(x,y,alpha=.05,CN=FALSE){
#
# Comparing two dependent correlations: Overlapping case
#
# x is assumed to be a matrix with 2 columns
#
#  Compare correlation of x[,1] with y to x[,2] with y
#
#  returns a confidence stored in 
#  ci
#
# This function is exactly like TWOpov, only it returns a p-value as well.
#
alph<-c(1:99)/100
for(i in 1:99){
irem<-i
chkit<-TWOpov(x,y,alpha=alph[i],CN=CN)$ci
if(sign(chkit[1]*chkit[2])==1)break
}
p.value<-irem/100
if(p.value<=.1){
iup<-(irem+1)/100
alph<-seq(.001,iup,.001)
for(i in 1:length(alph)){
p.value<-alph[i]
alph<-c(1:99)/100
for(i in 1:99){
irem<-i
chkit<-TWOpov(x,y,alpha=alph[i],CN=CN)$ci                    
if(sign(chkit[1]*chkit[2])==1)break   
}}}
p.value<-irem/100
if(p.value<=.1){
iup<-(irem+1)/100
alph<-seq(.001,iup,.001)
for(i in 1:length(alph)){
p.value<-alph[i]
chkit<-TWOpov(x,y,alpha=alph[i],CN=CN)$ci           
if(sign(chkit[1]*chkit[2])==1)break   
}}
if(p.value<=.001){
alph<-seq(.0001,.001,.0001)
for(i in 1:length(alph)){
p.value<-alph[i]
chkit<-TWOpov(x,y,alpha=alph[i],CN=CN)$ci         
if(sign(chkit[1]*chkit[2])==1)break  
}}
if(p.value<=.001){
alph<-seq(.0001,.001,.0001)
for(i in 1:length(alph)){
p.value<-alph[i]
chkit<-TWOpov(x,y,alpha=alph[i],CN=CN)$ci           
if(sign(chkit[1]*chkit[2])==1)break  
}}
res=TWOpov(x,y,alpha=alpha,CN=CN)
list(p.value=p.value,est.rho1=res$est.rho1,est.rho2=res$est.rho2,ci=res$ci)
}