Nothing
`p2colasr` <-
function (Z) {
#observed value
obs <- Z[1]
# sampling distribution
samp.d <- table(Z)/length(Z)
# number of possible outcomes
no <- length(samp.d)
# rank of the observed outcome
obs.o <- which(names(samp.d)==obs)
#probability of the observed outcome
p.obs <- samp.d[obs.o]
if (obs > mean(Z[-1])) {
# tail probability for the observed outcome
p.ge <- sum(samp.d[obs.o : no])
# which outcomes in the "other" tail are less probable than the observed outcome
other <- which(samp.d [1: (obs.o -1)] < p.obs)
# which is the least extreme outcome in the "other" tail that is less probable than the observed outcome
if(length(other)>0) {
least.o <- max(which(samp.d [1: (obs.o -1)] < p.obs))
# probability for the least extreme outcome
p.least <- samp.d [least.o]
}
# if none is "less", probable, p. least = 0
if(length(other)==0) p.least <- 0
}
if (obs < mean(Z[-1])) {
# tail probability for the observed outcome
p.ge <- sum(samp.d[1:obs.o])
# which outcomes in the "other" tail are less probable than the observed outcome
other <- which(samp.d [(obs.o +1):no] < p.obs)
# which is the least extreme outcome in the "other" tail that is less probable than the observed outcome
if(length(other)>0) {
least.o <- min(which(samp.d [(obs.o +1):no] < p.obs))
# probability for the least extreme outcome
p.least <- samp.d [least.o]
}
# if none is "less", probable, p. least = 0
if(length(other)==0) p.least <- 0
}
# 2-sided p-value
return( p.ge + p.least)
}
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