Nothing
cAnsBrad <-
function(alpha,m,n,method=NA,n.mc=10000){
pcalc <- function(q, m, n) .Call("pAnsari", q, m, n)
ccalc <- function(q, m, n) .Call("qAnsari", q, m, n)
N=m+n
if(alpha>1||alpha<0||!is.numeric(alpha)){
cat('Error: Check alpha value! \n')
return(alpha)
}
outp<-list()
outp$m<-m
outp$n<-n
outp$alpha<-alpha
outp$stat.name<-"Ansari-Bradley C"
outp$method<-method
if(is.na(outp$method)){
if(outp$m+outp$n<=200){
outp$method<-"Exact"
}
if(outp$m+outp$n>200){
outp$method<-"Asymptotic"
}
}
outp$two.sided<-1;
if(outp$method=="Monte Carlo"){
warning("The exact computation will work for large data, so Monte Carlo methods
are not recommended for this procedure.")
outp$method="Exact"
}
if(outp$method=="Exact"){
if(N%%2==0) tot<-N/2*(N/2+1)
if(N%%2==1) tot<-(N-1)/2*((N-1)/2+1)+(N+1)/2
outp$cutoff.U<-tot-ccalc(alpha,m,n)+1
outp$cutoff.L<-tot-ccalc(1-alpha,m,n)-1
outp$true.alpha.U<-pcalc(tot-outp$cutoff.U,m,n)
outp$true.alpha.L<-1-pcalc(tot-outp$cutoff.L-1,m,n)
}
if(outp$method=="Asymptotic"){
if(N%%2==0){
exp_C=n*(N+2)/4
var_C=m*n*(N+2)*(N-2)/(48*(N-1))
}
if(N%%2==1){
exp_C=n*(N+1)^2/(4*N)
var_C=m*n*(N+1)*(3+N^2)/(48*N^2)
}
outp$cutoff.L=exp_C+qnorm(alpha)*(var_C)^(1/2)
outp$cutoff.U=exp_C+qnorm(1-alpha)*(var_C)^(1/2)
}
class(outp)<-"NSM3Ch5c"
outp
}
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