R/grit.R

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

grit <-
function(x,y,itest=1,sm.fun=rplot,nboot=500,alpha=.05,SEED=TRUE,
fr=1,plot.fun=rplot,plotit=TRUE,...){
#
# Fit a running interval smoother using projection distances
# excluding the predictor variable itest
# itest=1 by default, meaning that the goal is to test
# the hypothesis that the first variable does not contribute
# to the regression model
#
# Method fits a smooth using x_1, ..., x_p, excluding variabe itest
# Then x_itest and the resulting residuals are passed to indt
# Alternative choices for smooth include
# sm.fun=lplot, and if p>2, runpd
#
if(!is.matrix(x))stop("Should have two or more predictors stored in a matrix")
p<-ncol(x)
pp<-p+1
x<-elimna(cbind(x,y))
y<-x[,pp]
x<-x[,1:p]
flag<-rep(T,ncol(x))
flag[itest]<-F
temp<-sm.fun(x[,flag],y,plotit=FALSE,pyhat=TRUE,fr=fr)
res<-y-temp
test.it<-indt(x[,itest],res)
if(plotit)plot.fun(x[,itest],res,...)
test.it
}