get_fitted_g

get_lfdr

get_lfsr

get_logLR

get_loglik

get_np

get_pi0

get_pm

get_pp

get_psd

get_qvalue

get_svalue


These functions simply return elements of an ash object, generally without doing any calculations. 
(So if the value was not computed during the original call to ash, eg because of how outputlevel was set in the call, 
then NULL will be returned.)
Accessing elements in this way
rather than directly from the ash object will help ensure compatability moving forward
(e.g. if the internal structure of the ash object changes during software development.)


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.

Peter Carbonetto

ashr

Methods for Adaptive Shrinkage, using Empirical Bayes

get_lfsr function

<ul>
<li> <code>get_lfsr</code>: local false sign rate </li>
<li> <code>get_lfdr</code>: local false discovery rate </li>
<li> <code>get_svalue</code>: svalue </li>
<li> <code>get_qvalue</code>: qvalue </li>
<li> <code>get_pm</code>: posterior mean </li>
<li> <code>get_psd</code>: posterior standard deviation </li>
<li> <code>get_pp</code>: positive probability </li>
<li> <code>get_np</code>: negative probability </li>
<li> <code>get_loglik</code>: log-likelihood </li>
<li> <code>get_logLR</code>: log-likelihood ratio </li>
<li> <code>get_fitted_g</code>: fitted g mixture </li>
<li> <code>get_pi0</code>: pi0, the proportion of nulls
</li>
</ul>

Functions

Return lfsr, lfdr, etc from ash object

get_lfsr: Return lfsr, lfdr, etc from ash object

Description

Usage

Arguments

Functions