ExGaussian

dexgaussian

pexgaussian

rexgaussian

x, q

Vector of means of the combined distribution.

Vector of standard deviations of the gaussian component.

sigma

Vector of scales of the exponential component.

beta

Logical; If <code>TRUE</code>, values are returned on the log scale.

Logical; If <code>TRUE</code> (default), return P(X &lt;= x). 
Else, return P(X &gt; x) .

lower.tail

log.p

Number of draws to sample from the distribution.

Density, distribution function, and random generation 
for the exponentially modified Gaussian distribution with
mean <code>mu</code> and standard deviation <code>sigma</code> of the gaussian 
component, as well as scale <code>beta</code> of the exponential
component.

Fit Bayesian generalized (non-)linear multivariate multilevel models
using 'Stan' for full Bayesian inference. A wide range of distributions
and link functions are supported, allowing users to fit -- among others --
linear, robust linear, count data, survival, response times, ordinal,
zero-inflated, hurdle, and even self-defined mixture models all in a
multilevel context. Further modeling options include non-linear and
smooth terms, auto-correlation structures, censored data, meta-analytic
standard errors, and quite a few more. In addition, all parameters of the
response distribution can be predicted in order to perform distributional
regression. Prior specifications are flexible and explicitly encourage
users to apply prior distributions that actually reflect their beliefs.
Model fit can easily be assessed and compared with posterior predictive
checks and leave-one-out cross-validation. References: B<c3><bc>rkner (2017)
<doi:10.18637/jss.v080.i01>; B<c3><bc>rkner (2018) <doi:10.32614/RJ-2018-017>;
Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.

ExGaussian: The Exponentially Modified Gaussian Distribution

Description

Usage

Arguments

Details