rtnorm: Random number generator for a truncated normal distribution

In konkam/BNPdensity: Ferguson-Klass Type Algorithm for Posterior Normalized Random Measures

Random number generator for a truncated normal distribution

Description

Generates a random number from a truncated normal distribution.

Usage

rtnorm(n, mean = 0, sd = 1, lower = -Inf, upper = Inf)

Details

For internal use

Note

Taken from msm R-package.

Author(s)

C. H. Jackson

Examples

## The function is currently defined as
function(n, mean = 0, sd = 1, lower = -Inf, upper = Inf) {
  if (length(n) > 1) {
    n <- length(n)
  }
  mean <- rep(mean, length = n)
  sd <- rep(sd, length = n)
  lower <- rep(lower, length = n)
  upper <- rep(upper, length = n)
  lower <- (lower - mean) / sd
  upper <- (upper - mean) / sd
  ind <- seq(length = n)
  ret <- numeric(n)
  alg <- ifelse(lower > upper, -1, ifelse(((lower < 0 & upper ==
    Inf) | (lower == -Inf & upper > 0) | (is.finite(lower) &
    is.finite(upper) & (lower < 0) & (upper > 0) & (upper -
    lower > sqrt(2 * pi)))), 0, ifelse((lower >= 0 & (upper >
    lower + 2 * sqrt(exp(1)) / (lower + sqrt(lower^2 + 4)) *
      exp((lower * 2 - lower * sqrt(lower^2 + 4)) / 4))),
  1, ifelse(upper <= 0 & (-lower > -upper + 2 * sqrt(exp(1)) / (-upper +
    sqrt(upper^2 + 4)) * exp((upper * 2 - -upper * sqrt(upper^2 +
    4)) / 4)), 2, 3)
  )))
  ind.nan <- ind[alg == -1]
  ind.no <- ind[alg == 0]
  ind.expl <- ind[alg == 1]
  ind.expu <- ind[alg == 2]
  ind.u <- ind[alg == 3]
  ret[ind.nan] <- NaN
  while (length(ind.no) > 0) {
    y <- rnorm(length(ind.no))
    done <- which(y >= lower[ind.no] & y <= upper[ind.no])
    ret[ind.no[done]] <- y[done]
    ind.no <- setdiff(ind.no, ind.no[done])
  }
  stopifnot(length(ind.no) == 0)
  while (length(ind.expl) > 0) {
    a <- (lower[ind.expl] + sqrt(lower[ind.expl]^2 + 4)) / 2
    z <- rexp(length(ind.expl), a) + lower[ind.expl]
    u <- runif(length(ind.expl))
    done <- which((u <= exp(-(z - a)^2 / 2)) & (z <= upper[ind.expl]))
    ret[ind.expl[done]] <- z[done]
    ind.expl <- setdiff(ind.expl, ind.expl[done])
  }
  stopifnot(length(ind.expl) == 0)
  while (length(ind.expu) > 0) {
    a <- (-upper[ind.expu] + sqrt(upper[ind.expu]^2 + 4)) / 2
    z <- rexp(length(ind.expu), a) - upper[ind.expu]
    u <- runif(length(ind.expu))
    done <- which((u <= exp(-(z - a)^2 / 2)) & (z <= -lower[ind.expu]))
    ret[ind.expu[done]] <- -z[done]
    ind.expu <- setdiff(ind.expu, ind.expu[done])
  }
  stopifnot(length(ind.expu) == 0)
  while (length(ind.u) > 0) {
    z <- runif(length(ind.u), lower[ind.u], upper[ind.u])
    rho <- ifelse(lower[ind.u] > 0, exp((lower[ind.u]^2 -
      z^2) / 2), ifelse(upper[ind.u] < 0, exp((upper[ind.u]^2 -
      z^2) / 2), exp(-z^2 / 2)))
    u <- runif(length(ind.u))
    done <- which(u <= rho)
    ret[ind.u[done]] <- z[done]
    ind.u <- setdiff(ind.u, ind.u[done])
  }
  stopifnot(length(ind.u) == 0)
  ret * sd + mean
}

konkam/BNPdensity documentation built on March 14, 2024, 7:15 a.m.