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# Function to create a vector to be used with the categorical distribution
# in BUGS to generate a discrete uniform prior
#
# Input variables
# A, B: range of the discrete uniform prior
#
# Written: September 2014, Michael Schaub
#
# Last up-date: 6.12.2019
#
##############################################################################
# dUnif0 <- function(A, B){
# pprob <- c(rep(0, A-1), rep(1/(B-A+1), (B-A+1)))
# return(pprob)
# }
# Proposed changes (by Mike):
# 1. Change arg names A, B to lower, upper (can be abbreviated).
# 2. Round input values
# 3. Vectorise: lower and/or upper can be vectors, in which case the function
# returns a matrix with a row corresponding to each element in the input.
dUnif <- function(lower, upper){
stopifnotEqualLength(lower, upper)
A <- round(lower) ; B <- round(upper)
nrow <- length(lower)
out <- matrix(0, nrow=nrow, ncol=max(B))
n <- B - A + 1 # number of non-zero values
for(i in 1:nrow)
out[i, A[i]:B[i]] <- rep(1/n[i], n[i])
return(drop(out))
}
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