my_dmvnorm.R

#'Copy of mvtnorm::dmvnorm for progiling and reference
#'
#'@param x matrix
#'@param mean vector
#'@param sigma covariance matrix
#'@param log logical. Default is \code{FALSE}
#'@param checkSymmetry logical. Default is \code{TRUE}
#'
#'@export
#'
my_dmvnorm <- function(x, mean = rep(0, p), sigma = diag(p), log = FALSE,
          checkSymmetry = TRUE){
  if (is.vector(x))
    x <- matrix(x, ncol = length(x))
  p <- ncol(x)
  if (!missing(mean)) {
    if (!is.null(dim(mean)))
      dim(mean) <- NULL
    if (length(mean) != p)
      stop("x and mean have non-conforming size")
  }
  if (!missing(sigma)) {
    if (p != ncol(sigma))
      stop("x and sigma have non-conforming size")
    if (checkSymmetry && !isSymmetric(sigma, tol = sqrt(.Machine$double.eps),
                                      check.attributes = FALSE))
      stop("sigma must be a symmetric matrix")
  }
  dec <- tryCatch(base::chol(sigma), error = function(e) e)
  if (inherits(dec, "error")) {
    x.is.mu <- colSums(t(x) != mean) == 0
    logretval <- rep.int(-Inf, nrow(x))
    logretval[x.is.mu] <- Inf
  }
  else {
    tmp <- backsolve(dec, t(x) - mean, transpose = TRUE)
    rss <- colSums(tmp^2)
    logretval <- -sum(log(diag(dec))) - 0.5 * p * log(2 *
                                                        pi) - 0.5 * rss
  }
  names(logretval) <- rownames(x)
  if (log)
    logretval
  else exp(logretval)
}