Nothing
permER = function(target, dataset, xIndex, csIndex, wei = NULL, univariateModels=NULL, hash = FALSE, stat_hash=NULL, pvalue_hash=NULL,
threshold = 0.05, R= 999){
# Conditional independence test based on the Log Likelihood ratio test
if ( !survival::is.Surv(target) ) stop('The survival test can not be performed without a Surv object target');
csIndex[which(is.na(csIndex))] = 0;
thres <- threshold * R + 1
if ( hash ) {
csIndex2 = csIndex[which(csIndex!=0)]
csIndex2 = sort(csIndex2)
xcs = c(xIndex,csIndex2)
key = paste(as.character(xcs) , collapse=" ");
if (is.null(stat_hash[key]) == FALSE) {
stat = stat_hash[key];
pvalue = pvalue_hash[key];
results <- list(pvalue = pvalue, stat = stat, stat_hash=stat_hash, pvalue_hash=pvalue_hash);
return(results);
}
}
#initialization: these values will be returned whether the test cannot be carried out
pvalue = log(1)
stat = 0;
results <- list(pvalue = pvalue, stat = stat, stat_hash=stat_hash, pvalue_hash=pvalue_hash);
expo_results = NULL;
expo_results_full = NULL;
event = target[,2]
#retrieving the data
x = dataset[ , xIndex];
#if the censored indicator is empty, a dummy variable is created
numCases = dim(dataset)[1];
if ( length(event) == 0 ) event = vector('numeric',numCases) + 1;
if ( length(csIndex) == 0 || sum(csIndex == 0, na.rm = TRUE) > 0 ) {
expo_results <- survival::survreg(target ~ x, dist = "exponential", weights = wei)
dof <- length( coef(expo_results) ) - 1
stat = 2 * abs( diff(expo_results$loglik) )
if (stat > 0) {
step <- 0
j <- 1
n <- length(x)
while (j <= R & step < thres ) {
xb <- sample(x, n)
bit2 = survival::survreg(target ~ xb, dist = "exponential", weights = wei)
stat2 = 2 * abs( diff(bit2$loglik) )
step <- step + ( stat2 > stat )
j <- j + 1
}
pvalue <- log( (step + 1) / (R + 1) )
}
} else {
#fitting the full model
expo_results <- survival::survreg(target ~ ., data = as.data.frame(dataset[, csIndex]), dist = "exponential", weights = wei)
expo_results_full <- survival::survreg(target ~ ., data = as.data.frame( dataset[ , c(csIndex, xIndex)] ), dist = "exponential", weights = wei )
res = anova(expo_results, expo_results_full)
stat = abs( res[2, 6] );
if (stat > 0) {
xcs = dataset[, csIndex]
j <- 1
step <- 0
n <- length(x)
while (j <= R & step < thres ) {
xb <- sample(x, n)
bit2 = survival::survreg(target ~ ., data = as.data.frame( cbind(dataset[ , csIndex], xb) ), dist = "exponential", weights= wei )
step <- step + ( anova(expo_results, bit2)[2, 6] > stat )
j <- j + 1
}
pvalue <- log( (step + 1) / (R + 1) )
}
}
if ( is.na(pvalue) || is.na(stat) ) {
pvalue = log(1)
stat = 0;
} else {
#update hash objects
if( hash ) {
stat_hash[key] <- stat; #.set(stat_hash , key , stat)
pvalue_hash[key] <- pvalue; #.set(pvalue_hash , key , pvalue)
}
}
#testerrorcaseintrycatch(4);
results <- list(pvalue = pvalue, stat = stat, stat_hash=stat_hash, pvalue_hash=pvalue_hash);
return(results);
}
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