R/hc4qtest.R

In musto101/wilcox_R: What the package does (short line)

hc4qtest <-
function(x,y,k,nboot=500,SEED=TRUE){
#
# Test the hypothesis that a OLS slope is zero using HC4 wild bootstrap using quasi-t test.
# k is the index of coefficient being tested
#
if(SEED)set.seed(2)
x<-as.matrix(x)
# First, eliminate any rows of data with missing values.
temp <- cbind(x, y)
        temp <- elimna(temp)
        pval<-ncol(temp)-1
        x <- temp[,1:pval]
        y <- temp[, pval+1]
x<-as.matrix(x)
p<-ncol(x)
pp<-p+1
temp<-lsfit(x,y)
yhat<-mean(y)
res<-y-yhat
s<-lsfitNci4(x, y)$cov[-1, -1]
s<-as.matrix(s)
si<-s[k,k]
b<-temp$coef[2:pp]
qtest<-b[k]/sqrt(si)
data<-matrix(runif(length(y)*nboot),nrow=nboot)
data<-(data-.5)*sqrt(12) # standardize the random numbers.
rvalb<-apply(data,1,lsqtest4,yhat,res,x, k)
sum<-sum(abs(rvalb)>= abs(qtest[1]))
p.val<-sum/nboot
list(p.value=p.val)
}