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https://github.com/cran/RcppDist
24 June 2025, 10:44:38 UTC
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Tip revision: 284f8657fb9540fadcc77f069db6a626bebf89b0 authored by JB Duck-Mayr on 28 October 2018, 21:50:09 UTC
version 0.1.1
Tip revision: 284f865
RcppDist-package.R
#' RcppDist
#'
#' 'Rcpp' Integration of Additional Probability Distributions
#'
#' The 'Rcpp' package provides a C++ library to make it easier to use C++ with
#' R. R and 'Rcpp' provide functions for a variety of statistical
#' distributions. Several R packages make functions available to R for
#' additional statistical distributions. However, to access these functions
#' from C++ code, a costly call to the R functions must be made.
#'
#' 'RcppDist' provides a header-only C++ library with functions for additional
#' statistical distributions that can be called from C++ when writing code
#' using 'Rcpp' or 'RcppArmadillo'. Functions are available that return a
#' 'NumericVector' as well as doubles, and for multivariate or matrix
#' distributions, 'Armadillo' vectors and matrices.
#' RcppDist provides functions for the following distributions:
#' \itemize{
#'   \item The four parameter beta distribution
#'   \item The location-scale t distribution
#'   \item The truncated normal distribution
#'   \item The truncated t distribution
#'   \item A truncated location-scale t distribution
#'   \item The triangle distribution
#'   \item The multivariate normal distribution*
#'   \item The multivariate t distribution*
#'   \item The Wishart distribution*
#'   \item And the inverse Wishart distribution*.
#' }
#'
#' Distributions marked with an asterisk rely also on RcppArmadillo.
#'
#' For more information on using 'RcppDist' functions in your C++ code, please
#' consult the vignette via \code{vignette("RcppDist")}; the vignette explains
#' how to link to the package and include the headers, which header files
#' provide which functions, and also provides all function declarations
#' (so that you can see the function and argument names and return/argument
#' types; the arguments are also described in reasonable detail). You can also
#' see an example of using the multivariate normal generator provided by
#' 'RcppDist' in the function \code{\link{bayeslm}}.
#'
#' @name RcppDist
#' @docType package
#' @author  JB Duck-Mayr
#' @useDynLib RcppDist
#' @importFrom Rcpp sourceCpp
NULL
.onUnload <- function (libpath) {
    library.dynam.unload('RcppDist', libpath)
}

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