skewnorm: Skew normal distribution

In LaMa: Fast Numerical Maximum Likelihood Estimation for Latent Markov Models

Skew normal distribution

Description

Density, distribution function, quantile function and random generation for the skew normal distribution.

Usage

dskewnorm(x, xi = 0, omega = 1, alpha = 0, log = FALSE)

pskewnorm(q, xi = 0, omega = 1, alpha = 0, lower.tail = TRUE, log.p = FALSE)

qskewnorm(p, xi = 0, omega = 1, alpha = 0, lower.tail = TRUE, log.p = FALSE)

rskewnorm(n, xi = 0, omega = 1, alpha = 0)

Arguments

x, q	vector of quantiles
xi	location parameter
omega	scale parameter, must be positive.
alpha	skewness parameter, +/- Inf is allowed.
log, log.p	logical; if TRUE, probabilities/ densities p are returned as \log(p).
lower.tail	logical; if TRUE (default), probabilities are P[X \le x], otherwise P[X > x].
p	vector of probabilities
n	number of observations. If length(n) > 1, the length is taken to be the number required.

Details

This implementation of dskewnorm allows for automatic differentiation with RTMB while the other functions are imported from the sn package.

Value

dskewnorm gives the density, pskewnorm gives the distribution function, qskewnorm gives the quantile function, and rskewnorm generates random deviates.

Examples

x = rskewnorm(1)
d = dskewnorm(x)
p = pskewnorm(x)
q = qskewnorm(p)

LaMa documentation built on July 25, 2026, 1:08 a.m.