# SkewNormal: The Skew-Normal Distribution In brms: Bayesian Regression Models using 'Stan'

## Description

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

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34``` ```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 Aug. 23, 2021, 5:08 p.m.