as.theta.vcov

Get theta parameterisation of a covariance structure

Fit linear and generalized linear mixed models with various
extensions, including zero-inflation. The models are fitted using maximum
likelihood estimation via 'TMB' (Template Model Builder). Random effects are
assumed to be Gaussian on the scale of the linear predictor and are integrated
out using the Laplace approximation. Gradients are calculated using automatic
differentiation.

Mollie Brooks

glmmTMB

Generalized Linear Mixed Models using Template Model Builder

Ben Bolker

Kasper Kristensen

Martin Maechler

Arni Magnusson

Maeve McGillycuddy

Hans Skaug

Anders Nielsen

Casper Berg

Koen van Bentham

Nafis Sadat

Daniel Lüdecke

Russ Lenth

Joseph O'Brien

Charles J. Geyer

Mikael Jagan

Brenton Wiernik

Daniel B. Stouffer

Michael Agronah

as.theta.vcov function

<dl><dt>Sigma</dt>
<dd>a covariance matrix</dd>
<dt>corrs.only</dt>
<dd>return only values corresponding to the correlation matrix parameters?</dd></dl>

Arguments

Get theta parameterisation of a covariance structure — as.theta.vcov

<dl>

<dt>Sigma</dt>
<dd>a covariance matrix</dd>


<dt>corrs.only</dt>
<dd>return only values corresponding to the correlation matrix parameters?</dd>

</dl>

Get theta parameterisation of a covariance structure

as.theta.vcov: Get theta parameterisation of a covariance structure

Description

Usage

Value

Arguments