vcov.Model

Returns the variance-covariance matrix for a `Model` object. Specifically, this function will 
return the inverse GLS information matrix for the fixed effect parameters. Small sample corrections 
can be accessed directly from the Model using `Model$small_sample_correction()`. The varaince-covariance 
matrix including the random effects can be accessed using `Model$information_matrix(include.re = TRUE)`.

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

vcov.Model function

<dl><dt>object</dt>
<dd>A `Model` object.</dd>
<dt>...</dt>
<dd>Further arguments passed from other methods</dd></dl>

Arguments

Calculate Variance-Covariance matrix for a `Model` object — vcov.Model

<dl>

<dt>object</dt>
<dd>A `Model` object.</dd>


<dt>...</dt>
<dd>Further arguments passed from other methods</dd>

</dl>

vcov.Model: Calculate Variance-Covariance matrix for a `Model` object

Description

Usage

Value

Arguments