simulate.ebnm

The <code><a href="/link/simulate?package=ebnm&version=1.1-2" data-mini-rdoc="ebnm::simulate">simulate</a></code> method for class <code>ebnm</code>.
 Extracts the posterior sampler from an object of class <code>ebnm</code>
 and returns a specified number of samples.

Provides simple, fast, and stable functions to fit the normal
means model using empirical Bayes. For available models and details, see
function ebnm(). A detailed introduction to the package is provided
by Willwerscheid and Stephens (2021) <arXiv:2110.00152>.

Peter Carbonetto

ebnm

Solve the Empirical Bayes Normal Means Problem

Jason Willwerscheid

Matthew Stephens

Andrew Goldstein

Yusha Liu

simulate.ebnm function

<dl><dt>object</dt>
<dd>The fitted <code>ebnm</code> object.</dd>
<dt>nsim</dt>
<dd>The number of posterior samples to return per observation.</dd>
<dt>seed</dt>
<dd>Either <code>NULL</code> or an integer that will be used in a call to
<code>set.seed</code> before simulating. If set, the value is saved as the
<code>"seed"</code> attribute of the returned value. The default, <code>NULL</code>,
will not change the random generator state.</dd>
<dt>...</dt>
<dd>Additional arguments to be passed to the posterior sampler
function. Since <code>ebnm_horseshoe</code> returns an MCMC sampler, it takes
parameter <code>burn</code>, the number of burn-in samples to discard. At
present, no other samplers take any additional parameters.</dd></dl>

Arguments

The <code><a href='https://rdrr.io/r/stats/simulate.html'>simulate</a></code> method for class <code>ebnm</code>.
 Extracts the posterior sampler from an object of class <code>ebnm</code>
 and returns a specified number of samples.

Sample from the posterior of a fitted EBNM model — simulate.ebnm

<dl>

<dt>object</dt>
<dd>The fitted <code>ebnm</code> object.</dd>


<dt>nsim</dt>
<dd>The number of posterior samples to return per observation.</dd>


<dt>seed</dt>
<dd>Either <code>NULL</code> or an integer that will be used in a call to
<code>set.seed</code> before simulating. If set, the value is saved as the
<code>"seed"</code> attribute of the returned value. The default, <code>NULL</code>,
will not change the random generator state.</dd>


<dt>...</dt>
<dd>Additional arguments to be passed to the posterior sampler
function. Since <code>ebnm_horseshoe</code> returns an MCMC sampler, it takes
parameter <code>burn</code>, the number of burn-in samples to discard. At
present, no other samplers take any additional parameters.</dd>

</dl>

simulate.ebnm: Sample from the posterior of a fitted EBNM model

Description

Usage

Value

Arguments