R/vtn.R

In RcppTN: Rcpp-Based Truncated Normal Distribution RNG and Family

##' Calculate variance 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 Variance
##' @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
##' vtn() ## 1
##' vtn(0, 1, -Inf, Inf) ## 1
##' vtn(0, 1, -9999, 9999) ## 1
##'
##' vtn(0, 1, 0, Inf) ## 0.36338
##'
##' vtn(0, 1, Inf, -Inf) ## NA with warning
##'
##' vtn(c(0, 0),
##'     c(1, 1),
##'     c(-Inf, 5),
##'     c(1, Inf)
##'     ) ## multiple variances
vtn <- 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("vtnRcpp",
                 mean = .mean,
                 sd = .sd,
                 low = .low,
                 high = .high
                 )
    if (.checks) {
        checkOutputs(out)
    }
    return(out)
}