Nothing
testIndRQ <- function(target, dataset, xIndex, csIndex, wei = NULL, univariateModels=NULL,
hash = FALSE, stat_hash=NULL, pvalue_hash=NULL) {
# 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.
# References
# [1] Koenker, Roger. Quantile regression. New York, Cambridge
# university press, 2005.
#initialization
#if the test cannot performed succesfully these are the returned values
pvalue <- log(1)
stat <- 0
csIndex[which(is.na(csIndex))] <- 0
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] <- log(1);#.set(pvalue_hash , key , 1)
}
results <- list(pvalue = log(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);
x <- dataset[ , xIndex];
cs <- dataset[ , csIndex];
#That means that the x variable does not add more information to our model due to an exact copy of this in the cs, so it is independent from the target
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] <- log(1);#.set(pvalue_hash , key , 1)
}
results <- list(pvalue = log(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] <- log(1);#.set(pvalue_hash , key , 1)
}
results <- list(pvalue = log(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 < quantreg::rq(target ~ 1, weights = wei)
fit2 <- quantreg::rq(target ~ x, weights = wei)
} else {
kapa <- length( csIndex )
ff1 <- as.formula(paste("target ~ ",paste("dataset[,",csIndex[1:kapa],"]",sep="",collapse="+"), sep=""))
ff2 <- as.formula(paste(paste("target ~ ",paste("dataset[,",csIndex[1:kapa],"]",sep="",collapse="+"), sep="") , "+dataset[,",xIndex,"]", sep = ""))
fit1 <- quantreg::rq( ff1, weights = wei )
fit2 <- quantreg::rq( ff2, weights= wei )
}
mod <- anova(fit1,fit2, test = "rank")
df1 <- as.numeric( mod[[1]][1] )
df2 <- as.numeric( mod[[1]][2] )
stat <- as.numeric( mod[[1]][3] )
pvalue <- pf(stat, df1, df2, lower.tail = FALSE, log.p = TRUE)
#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) {
#error case
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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