Nothing
##' Calculate expectation of Truncated Normal distributions
##'
##' The special values of -Inf and Inf are valid values in the .low and .high
##' arguments, respectively.
##'
##' @title Truncated Normal Distribution Expectation
##' @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 Length 1 logical vector indicating whether to perform checks
##' (safer) or not (faster) on the input parameters
##' @return A length K vector of expectations corresponding to the Truncated
##' Normal distributions. NAs are returned (with a warning) for invalid
##' parameter values.
##' @author Jonathan Olmsted
##' @examples
##' etn() ## 0
##' etn(0, 1, -Inf, Inf) ## 0
##' etn(0, 1, -9999, 9999) ## 0
##'
##' etn(0, 1, 0, Inf) ## 0.798
##'
##' etn(0, 1, Inf, -Inf) ## NA with warning
##'
##' etn(c(0, 0),
##' c(1, 1),
##' c(-Inf, 5),
##' c(1, Inf)
##' ) ## multiple expectations
##'
##'
etn <- function(.mean = rep(0, 1),
.sd = rep(1, length(.mean)),
.low = rep(-Inf, length(.mean)),
.high = rep(Inf, length(.mean)),
.checks = TRUE
) {
if (.checks) {
checkInputs(.mean, .sd, .low, .high)
}
out <- .Call("etnRcpp",
mean = .mean,
sd = .sd,
low = .low,
high = .high
)
if (.checks) {
checkOutputs(out)
}
return(out)
}
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