R/prplot.R

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

prplot <-
function(x,y,pval=ncol(x),regfun=tsreg,fr=.8,est=onestep,op=1,
xlab="X",ylab="Residuals",xout=FALSE,outfun=out,...){
#
# Goal: check for curvature associated with predictor
# indicated by pval.
# This is done by creating a partial residual plot.
# That is subtracting out the linear prediction based
# on the other predictors and then
# smooth the result versus the predictor in the column of x indicated by pval
#
x=as.matrix(x)
p=ncol(x)
p1=p+1
temp=elimna(cbind(x,y))
x=temp[,1:p]
y=temp[,p1]
if(xout){
flag<-outfun(x,...)$keep
x<-as.matrix(x)
x<-x[flag,]
y<-y[flag]
x<-as.matrix(x)
}
if(!is.matrix(x))stop("Should have two or more variables stored in a matrix")
flag<-rep(T,ncol(x))
flag[pval]<-F
temp<-regfun(x[,flag],y)$residual
if(op!=1)rungen(x[,!flag],temp,est=est,fr=fr,xlab=xlab,ylab=ylab,...)
if(op==1)lplot(x[,!flag],temp,xlab=xlab,ylab=ylab)
}