posterior.mode

Estimates the marginal parameter modes using kernel density estimation

distribution

Fits Multivariate Generalised Linear Mixed Models (and related models) using Markov chain Monte Carlo techniques (Hadfield 2010 J. Stat. Soft.).

Jarrod Hadfield

MCMCglmm

MCMC Generalised Linear Mixed Models

posterior.mode function

<dl> <dt>x</dt>
<dd>mcmc object</dd> <dt>adjust</dt>
<dd>numeric, passed to <code><a href="/link/density?package=MCMCglmm&version=2.36" data-mini-rdoc="MCMCglmm::density">density</a></code> to adjust the bandwidth of the kernal density</dd> <dt>...</dt>
<dd>other arguments to be passed</dd></dl>

Arguments

Jarrod Hadfield <a href="/link/j.hadfield%40ed.ac.uk?package=MCMCglmm&version=2.36" data-mini-rdoc="MCMCglmm::j.hadfield@ed.ac.uk">j.hadfield@ed.ac.uk</a>

Author

Estimates the marginal parameter modes using kernel density estimation — posterior.mode

<dl>

 <dt>x</dt>
<dd>mcmc object</dd>

 <dt>adjust</dt>
<dd>numeric, passed to <code><a href='https://rdrr.io/r/stats/density.html'>density</a></code> to adjust the bandwidth of the kernal density</dd>

 <dt>...</dt>
<dd>other arguments to be passed</dd>

</dl>

Jarrod Hadfield <a href='mailto:j.hadfield@ed.ac.uk'>j.hadfield@ed.ac.uk</a>

posterior.mode: Estimates the marginal parameter modes using kernel density estimation

Description

Usage

Value

Arguments

Author

See Also

Examples