SkewNormal: The Skew-Normal Distribution

In brms: Bayesian Regression Models using 'Stan'

The Skew-Normal Distribution

Description

Density, distribution function, and random generation for the skew-normal distribution with mean mu, standard deviation sigma, and skewness alpha.

Usage

dskew_normal(
  x,
  mu = 0,
  sigma = 1,
  alpha = 0,
  xi = NULL,
  omega = NULL,
  log = FALSE
)

pskew_normal(
  q,
  mu = 0,
  sigma = 1,
  alpha = 0,
  xi = NULL,
  omega = NULL,
  lower.tail = TRUE,
  log.p = FALSE
)

qskew_normal(
  p,
  mu = 0,
  sigma = 1,
  alpha = 0,
  xi = NULL,
  omega = NULL,
  lower.tail = TRUE,
  log.p = FALSE,
  tol = 1e-08
)

rskew_normal(n, mu = 0, sigma = 1, alpha = 0, xi = NULL, omega = NULL)

Arguments

x, q	Vector of quantiles.
mu	Vector of mean values.
sigma	Vector of standard deviation values.
alpha	Vector of skewness values.
xi	Optional vector of location values. If NULL (the default), will be computed internally.
omega	Optional vector of scale values. If NULL (the default), will be computed internally.
log	Logical; If TRUE, values are returned on the log scale.
lower.tail	Logical; If TRUE (default), return P(X <= x). Else, return P(X > x) .
log.p	Logical; If TRUE, values are returned on the log scale.
p	Vector of probabilities.
tol	Tolerance of the approximation used in the computation of quantiles.
n	Number of draws to sample from the distribution.

Details

See vignette("brms_families") for details on the parameterization.

brms documentation built on Sept. 23, 2024, 5:08 p.m.