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##' Calculate density of Truncated Normal distributions
##'
##' @title Truncated Normal Distribution Density
##' @param .x Length K vector of the points at which to evaluate the density
##' @param .mean Length K vector with the means of the K Normal distributions
##' *prior* to truncation
##' @param .sd Length K vector with the standard deviations of the K Normal
##' distributions *prior* to truncation
##' @param .low Length K vector with the lower truncation bound of the K Normal
##' distributions *prior* to truncation
##' @param .high Length K vector with the upper truncation bound of the K Normal
##' distributions *prior* to truncation
##' @param .checks Logical indicating whether inputs and outputs should be
##' checked and either stop (for bad inputs) or warn (for likely bad outputs)
##' @return Length K vector with the entropies associated with each of the K
##' Truncated Normal distributions
##' @author Jonathan Olmsted
##' @examples
##' lows <- c(-1, 5, -100, 4, 4, -100, 7)
##' highs <- c(1, 100, 10, 7, 4.1, 100, 100)
##' dtn(.x = rep(0, length(lows)),
##' .mean = rep(0, length(lows)),
##' .sd = rep(1, length(lows)),
## .low = lows,
##' .high = highs
##' )
dtn <- function(.x = 0,
.mean = rep(0, length(.x)),
.sd = rep(1, length(.x)),
.low = rep(-Inf, length(.x)),
.high = rep(Inf, length(.x)),
.checks = TRUE
) {
if (.checks) {
checkInputs(.mean, .sd, .low, .high)
}
out <- .Call("dtnRcpp",
x = .x,
mean = .mean,
sd = .sd,
low = .low,
high = .high
)
if (.checks) {
checkOutputs(out)
}
return(out)
}
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