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

 SkewNormal R Documentation

## 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. 19, 2022, 5:06 p.m.