GSAfisher.GSAfisher.mult <-
function(p) {
if (!inherits(p, "GSAfisher.mult"))
stop("x must be an object of class 'GSAfisher.mult'")
if (is.null(dim(p))){
output <- data.frame( InputDataPos= numeric(), Statistical = numeric(), k = numeric(),
DegreesFreedom= numeric(), pvalue= numeric())
c=0
for (i in p){
c=c+1
if(any(!(i>0 & i<1)))
warning("The element", c ," in the imput have a wrong pvalue",noBreaks. = TRUE)
S<-(sum(log(i))*-2)
k<-length(i)
df<-k*2
pval<- pchisq(S, df=df, lower.tail=F)
#confidence interval.
output[c,]<-c(c,S, k, df, pval)
}
}else{ ### Esto esta en proceso
if(any(!(p>0 & p<1))){
col<-which(!(p>0 & p<1),arr.ind = F)[,2]
warning("The element ", col ," does not contain real pvalues" )
}
info<-apply(p,2,function(x) {x_gsa<-loadGSAfisher(x);GSAfisher(x_gsa)})
name_GSA<-lapply(info, function(x) x$DataName)
Stat<-lapply(info, function(x) x$FisherCombinedStatistic)
K<-lapply(info, function(x) x$Tests)
df<-lapply(info, function(x) x$Degreesoffreedom)
pval<-lapply(info, function(x) x$p.value)
output<-data.frame(InputDataPos= unlist(name_GSA) ,Statistical=unlist(Stat),
k= unlist(K), DegreesFreedom=unlist(df),pvalue=unlist(pval))
}
class(output)<-c("GSAfisher.mult","data.frame")
return(output)
}
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