hnorm: Half-Normal distribution

hnormR Documentation

Half-Normal distribution

Description

Probability density function (PDF), cummulative density function (CDF), quantile function and random generation for the Half-normal (hnorm) distribution.

Usage

dhnorm(x, theta = 1, mu = 0, log = FALSE)

phnorm(q, theta = 1, mu = 0, lower.tail = TRUE, log.p = FALSE)

qhnorm(p, theta = 1, mu = 0, sigma = NULL, lower.tail = TRUE, log.p = FALSE)

rhnorm(n, theta = 1, mu = 0)

theta2sigma(theta)

sigma2theta(sigma)

Arguments

x, q

numeric vector, x > \mu and q > \mu

theta

numerical parameter, strictly positive (default 1).

mu

location parameter (\mu).

lower.tail

logical; if TRUE (default), probabilities are P[X<=x], otherwise, P[X > x]

log.p

logical; if TRUE, probabilities/densities p are returned as log(p).

sigma

Standard deviation of the normal distribution. Here, \sigma = \sqrt \pi/(\theta\sqrt 2)

n

number of observations

Details

An alternative parameterization to avoid issues when sigma is near zero is applied by using a scaled precision (inverse of the variance) obtained by setting \theta = \sqrt(\pi)/(\sigma*\sqrt(2)). Details about these functions can be found in Wikipedia and in MathWorld and MathWorks to see the distribution with location parameter \mu. Notice that \theta = 1 means \sigma = \sqrt \pi/\sqrt 2.

Value

Half-normal PDF values (theta parameter) for dhnorm, Half-normal probability for phnorm, quantiles or Half-normal random generated values for rhnorm.

Author(s)

Robersy Sanchez (https://genomaths.com).

Examples

set.seed(123) # set a seed
sigma <- 1.2
theta <- sigma2theta(sigma)
x <- rhnorm(n = 1e5, theta = theta)
hist(x, 100, freq = FALSE)
curve(dhnorm(x, theta = theta), col = "red", add = TRUE)

#' # Checking the function outputs for the logarithms of probabilities
x <- rhnorm(n = 10, theta = sigma2theta(2))
x1 <- phnorm(x, theta = sigma2theta(2), log = TRUE)
x2 <- phnorm(x, theta = sigma2theta(2), log = FALSE)
all(round(x1, 8) == round(log(x2), 8))

x3 <- dhnorm(x, theta = sigma2theta(2), log = TRUE)
x4 <- dhnorm(x, theta = sigma2theta(2), log = FALSE)
all(round(x3, 8) == round(log(x4), 8))

genomaths/usefr documentation built on April 18, 2023, 3:35 a.m.