get_post_sample

Returns random samples from the posterior distribution for each
 observation in an ash object. A matrix is returned, with columns corresponding
 to observations and rows corresponding to samples.

The R package 'ashr' implements an Empirical Bayes
approach for large-scale hypothesis testing and false discovery
rate (FDR) estimation based on the methods proposed in
M. Stephens, 2016, "False discovery rates: a new deal",
<DOI:10.1093/biostatistics/kxw041>. These methods can be applied
whenever two sets of summary statistics---estimated effects and
standard errors---are available, just as 'qvalue' can be applied
to previously computed p-values. Two main interfaces are
provided: ash(), which is more user-friendly; and ash.workhorse(),
which has more options and is geared toward advanced users. The
ash() and ash.workhorse() also provides a flexible modeling
interface that can accommodate a variety of likelihoods (e.g.,
normal, Poisson) and mixture priors (e.g., uniform, normal).

Peter Carbonetto

ashr

Methods for Adaptive Shrinkage, using Empirical Bayes

Matthew Stephens

Chaoxing Dai

David Gerard

Mengyin Lu

Lei Sun

Jason Willwerscheid

Nan Xiao

Mazon Zeng

get_post_sample function

<dl><dt>a</dt>
<dd>the fitted ash object</dd>
<dt>nsamp</dt>
<dd>number of samples to return (for each observation)</dd></dl>

Arguments

Sample from posterior — get_post_sample

<dl>

<dt>a</dt>
<dd>the fitted ash object</dd>


<dt>nsamp</dt>
<dd>number of samples to return (for each observation)</dd>

</dl>

Sample from posterior

get_post_sample: Sample from posterior

Description

Usage

Arguments

Examples