R/sedm.R

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

sedm <-
function(x,y=NA,q=.5){
#
# Let D=X_m-Y_m be the difference between
# mth order statistics where X and Y are dependent.
# Estimate standard error D with m=[qn+.5]
# using adaptive kernel method
#
# This function is used by qdtest
#
x<-as.matrix(x)
if(is.na(y[1]))y<-x[,2]
x<-x[,1]
n<-length(x)
m<-floor(q*n+.5)
yord<-sort(y)
flag<-(y<=yord[m])
xord<-sort(x)
xq<-xord[m]
yord<-sort(y)
yq<-yord[m]
flag1<-(x<=xq)
flag2<-(y<=yq)
A<-mean(flag1*flag2)
flag1<-(x<=xq)
flag2<-(y>yq)
B<-mean(flag1*flag2)
flag1<-(x>xq)
flag2<-(y<=yq)
C1<-mean(flag1*flag2)
flag1<-(x>xq)
flag2<-(y>yq)
D1<-mean(flag1*flag2)
fx<-akerd(x,pts=xq,plotit=FALSE,pyhat=T)
fy<-akerd(y,pts=yq,plotit=FALSE,pyhat=T)
v1<-(q-1)^2*A
v2<-(q-1)*q*B
v3<-(q-1)*q*C1
v4<-q*q*D1
temp<-0-2*(v1+v2+v3+v4)/(fx*fy)+q*(1-q)/fx^2+q*(1-q)/fy^2
val<-sqrt(temp/n)
val
}