Is an implementation of a density function for a logit-normal distribution available in R?

Question

Is an implementation of a density function for a logit-normal distribution available in R?

I have not found one in a package or in the CRAN task view of probability distributions.

This is for a MLE fitting of a function to data.

Answer 1

Bare-bones scaled logit-normal distribution code, use at your own risk:

logit <- function(x, a = 0, b = 1) 
{
  stopifnot(a < b)
  x <- (x - a)/(b - a)
  log(x) - log(1 - x)
}

invlogit <- function(x, a = 0, b = 1)
{
  stopifnot(a < b)
  ((b - a)/(1 + exp(-x))) + a
}

dlogitnorm <- function(x, ..., a = 0, b = 1, log = FALSE)
{
  out <- dnorm(x = logit(x, a, b), ..., log = TRUE) + log(b - a) - log(x - a) - log(b - x)
  out[x == a | x == b] <- -Inf
  if(log) out else exp(out)
}

plogitnorm <- function(q, ..., a = 0, b = 1, lower.tail = TRUE, log.p = FALSE)
  pnorm(logit(q, a, b)), ..., lower.tail = lower.tail, log.p = log.p)

qlogitnorm <- function(p, ..., a = 0, b = 1, lower.tail = TRUE, log.p = FALSE)
  invlogit(qnorm(p, ..., lower.tail = lower.tail, log.p = log.p), a, b)

rlogitnorm <- function(n, ..., a = 0, b = 1) invlogit(rnorm(n, ....), a, b)

Answer 2

The logitnorm package on R-Forge appears to do what you want.