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#' Location-scale version of the t-distribution
#'
#' Probability mass function, distribution function and random generation
#' for location-scale version of the t-distribution. Location-scale version
#' of the t-distribution besides degrees of freedom \eqn{\nu}, is parametrized
#' using additional parameters \eqn{\mu} for location and \eqn{\sigma} for
#' scale (\eqn{\mu = 0} and \eqn{\sigma = 1} for standard t-distribution).
#'
#' @param x,q vector of quantiles.
#' @param p vector of probabilities.
#' @param n number of observations. If \code{length(n) > 1},
#' the length is taken to be the number required.
#' @param mu vector of locations
#' @param sigma vector of positive valued scale parameters.
#' @param df degrees of freedom (> 0, maybe non-integer). \code{df = Inf} is allowed.
#' @param log,log.p logical; if TRUE, probabilities p are given as log(p).
#' @param lower.tail logical; if TRUE (default), probabilities are \eqn{P[X \le x]}
#' otherwise, \eqn{P[X > x]}.
#'
#' @seealso \code{\link[stats]{TDist}}
#'
#' @examples
#'
#' x <- rlst(1e5, 1000, 5, 13)
#' hist(x, 100, freq = FALSE)
#' curve(dlst(x, 1000, 5, 13), -60, 60, col = "red", add = TRUE)
#' hist(plst(x, 1000, 5, 13))
#' plot(ecdf(x))
#' curve(plst(x, 1000, 5, 13), -60, 60, col = "red", lwd = 2, add = TRUE)
#'
#' @name LocationScaleT
#' @aliases LocationScaleT
#' @aliases dlst
#'
#' @keywords distribution
#' @concept Univariate
#' @concept Continuous
#'
#' @export
dlst <- function(x, df, mu = 0, sigma = 1, log = FALSE) {
cpp_dlst(x, df, mu, sigma, log[1L])
}
#' @rdname LocationScaleT
#' @export
plst <- function(q, df, mu = 0, sigma = 1, lower.tail = TRUE, log.p = FALSE) {
cpp_plst(q, df, mu, sigma, lower.tail[1L], log.p[1L])
}
#' @rdname LocationScaleT
#' @export
qlst <- function(p, df, mu = 0, sigma = 1, lower.tail = TRUE, log.p = FALSE) {
cpp_qlst(p, df, mu, sigma, lower.tail[1L], log.p[1L])
}
#' @rdname LocationScaleT
#' @export
rlst <- function(n, df, mu = 0, sigma = 1) {
if (length(n) > 1) n <- length(n)
cpp_rlst(n, df, mu, sigma)
}
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