Nothing
permRQ = function(target, dataset, xIndex, csIndex, wei = NULL, univariateModels=NULL, hash = FALSE, stat_hash=NULL,
pvalue_hash=NULL, threshold = 0.05, R = 999) {
# TESTINDRQ Conditional Independence Test for numerical class variables
# PVALUE = TESTINDRQ(Y, DATA, XINDEX, CSINDEX)
# This test provides a p-value PVALUE for the NULL hypothesis H0 which is
# X is independent by TARGET given CS. The pvalue is calculated following
# nested models
# This method requires the following inputs
# TARGET: a numeric vector containing the values of the target (numerical) variable.
# Its support can be R or any number betweeen 0 and 1, i.e. it contains proportions.
# DATASET: a numeric data matrix containing the variables for performing the test. They can be mixed variables.
# XINDEX: the index of the variable whose association with the target we want to test.
# CSINDEX: the indices if the variable to condition on.
# this method returns: the pvalue PVALUE, the statistic STAT.
#if the test cannot performed succesfully these are the returned values
pvalue = log(1)
stat = 0;
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);
}
}
#if the xIndex is contained in csIndex, x does not bring any new
#information with respect to cs
if ( !is.na( match(xIndex, csIndex) ) ) {
if( hash ) { #update hash objects
stat_hash[key] <- 0;#.set(stat_hash , key , 0)
pvalue_hash[key] <- 1;#.set(pvalue_hash , key , 1)
}
results <- list(pvalue = 1, stat = 0, stat_hash=stat_hash, pvalue_hash=pvalue_hash);
return(results);
}
#check input validity
if ( any(xIndex < 0) || any(csIndex < 0) ) {
message(paste("error in testIndRQ : wrong input of xIndex or csIndex"))
results <- list(pvalue = pvalue, stat = stat, stat_hash=stat_hash, pvalue_hash=pvalue_hash);
return(results);
}
xIndex = unique(xIndex);
csIndex = unique(csIndex);
#extract the data
x = dataset[ , xIndex];
cs = dataset[ , csIndex];
if ( length(cs) != 0 ) {
if ( is.null(dim(cs)[2]) ) { #cs is a vector
if (identical(x, cs) ) { #if(!any(x == cs) == FALSE)
if ( hash ) { #update hash objects
stat_hash[key] <- 0; #.set(stat_hash , key , 0)
pvalue_hash[key] <- 1; #.set(pvalue_hash , key , 1)
}
results <- list(pvalue = 1, stat = 0, stat_hash=stat_hash, pvalue_hash=pvalue_hash);
return(results);
}
} else { #more than one var
for (col in 1:dim(cs)[2]) {
if (identical(x, cs[, col]) ) { #if(!any(x == cs) == FALSE)
if ( hash ) { #update hash objects
stat_hash[key] <- 0;#.set(stat_hash , key , 0)
pvalue_hash[key] <- 1;#.set(pvalue_hash , key , 1)
}
results <- list(pvalue = 1, stat = 0, stat_hash=stat_hash, pvalue_hash=pvalue_hash);
return(results);
}
}
}
}
res <- tryCatch(
{
#if the conditioning set (cs) is empty, we use a simplified formula
if (length(cs) == 0) {
#compute the relationship between x,target directly
#fit1 = fita
fit1 = quantreg::rq(target ~ 1, weights = wei)
fit2 = quantreg::rq(target ~ x, weights = wei)
mod = anova(fit1, fit2, test = "rank")
stat = as.numeric( mod[[1]][3] )
step <- 0
j <- 1
n <- length(target)
while (j <= R & step < thres ) {
xb <- sample(x, n)
bit2 = quantreg::rq(target ~ xb, weights = wei )
ww = anova(fit1, bit2, test = "rank")
step <- step + ( as.numeric( ww[[1]][3] ) > stat )
j <- j + 1
}
pvalue <- log( (step + 1) / (R + 1) )
} else {
fit1 = quantreg::rq( target ~ cs, weights = wei )
fit2 = quantreg::rq( target ~ cs + x, weights = wei )
mod = anova(fit1, fit2, test = "rank")
stat = as.numeric( mod[[1]][3] )
step <- 0
j <- 1
n <- length(target)
while (j <= R & step < thres ) {
xb <- sample(x, n)
bit2 = quantreg::rq(target ~ cs + xb, weights = wei )
ww = anova(fit1, bit2, test = "rank")
step <- step + ( as.numeric( ww[[1]][3] ) > stat )
j <- j + 1
}
pvalue <- log( (step + 1) / (R + 1) )
}
#last error check
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);
},
error=function(cond) {
pvalue = log(1)
stat = 0;
results <- list(pvalue = pvalue, stat = stat, stat_hash=stat_hash, pvalue_hash=pvalue_hash);
return(results);
},
finally={}
)
return(res);
}
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