brms: SkewNormal – R documentation

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SkewNormal

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 samples to draw from the distribution.

Details

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

brms

Bayesian Regression Models using 'Stan'

v2.15.0

GPL-2

Authors

Paul-Christian Bürkner [aut, cre], Jonah Gabry [ctb], Sebastian Weber [ctb], Andrew Johnson [ctb], Martin Modrak [ctb]

Initial release

2021-03-10