Quantile

Skeleton list to declare a quantile regression model in a `Model` object.

Specification, analysis, simulation, and fitting of generalised linear mixed models.
Includes Markov Chain Monte Carlo Maximum likelihood and Laplace approximation model fitting for a range of models,
non-linear fixed effect specifications, a wide range of flexible covariance functions that can be combined arbitrarily,
robust and bias-corrected standard error estimation, power calculation, data simulation, and more.
See <https://samuel-watson.github.io/glmmr-web/> for a detailed manual.

Sam Watson

glmmrBase

Generalised Linear Mixed Models in R

Quantile function

<dl><dt>link</dt>
<dd>Name of the link function - any of `identity`, `log`, `logit`, `inverse`, or `probit`</dd>
<dt>scaled</dt>
<dd>Logical indicating whether to include a scale parameter. If FALSE then the scale parameter is one.</dd>
<dt>q</dt>
<dd>Scalar in [0,1] declaring the quantile of interest.</dd></dl>

Arguments

Family declaration to support quantile regression — Quantile

<dl>

<dt>link</dt>
<dd>Name of the link function - any of `identity`, `log`, `logit`, `inverse`, or `probit`</dd>


<dt>scaled</dt>
<dd>Logical indicating whether to include a scale parameter. If FALSE then the scale parameter is one.</dd>


<dt>q</dt>
<dd>Scalar in [0,1] declaring the quantile of interest.</dd>

</dl>

Quantile: Family declaration to support quantile regression

Description

Usage

Value

Arguments