R/lnorm2.R

In thiyangt/fformpp: Feature-based FORecast Model Performance Prediction

##' Alternative parametrization of log normal distribution.
##'
##' See help("rlnorm") for the details for the log-normal distribution.
##' @title Log-normal distribution with alternative parametrization.
##' @param mean "vector" the mean value of the log-normal distribution.
##' @param sd "vector" the variance of the log-normal distribution.
##' @return See the corresponding help for the usual log-normal functions.
##' @references Li Villani Kohn 2010.
##' @author Feng Li, Department of Statistics, Stockholm University, Sweden.
##' @note Created: Fri Mar 16 17:59:11 CET 2012;
##'       Current: Fri Mar 16 17:59:18 CET 2012.
##' @export
rlnorm2 <- function(n, mean, sd)
  {
    var <- sd^2
    s2 <- log(var/mean^2+1)
    m <- log(mean) - s2/2
    out <- rlnorm(n = n, meanlog = m, sdlog = sqrt(s2))
    return(out)
  }
dlnorm2 <- function(x, mean, sd, log = FALSE)
  {
    var <- sd^2
    s2 <- log(var/mean^2+1)
    m <- log(mean) - s2/2
    out <- dlnorm(x = x, meanlog = m, sdlog = sqrt(s2), log = log)
    return(out)
  }
plnorm2 <- function(q, mean, sd, lower.tail = TRUE, log.p = FALSE)
  {
    var <- sd^2
    s2 <- log(var/mean^2+1)
    m <- log(mean) - s2/2
    out <- plnorm(q = q, meanlog = m, sdlog = sqrt(s2),
                  lower.tail=lower.tail, log.p=log.p)
    return(out)
  }
qlnorm2 <- function(p, mean, sd, lower.tail = TRUE, log.p = FALSE)
  {
    var <- sd^2
    s2 <- log(var/mean^2+1)
    m <- log(mean) - s2/2
    out <- qlnorm(p = p, meanlog = m, sdlog = sqrt(s2),
                  lower.tail=lower.tail, log.p=log.p)
    return(out)
  }