dens

A mixture of k components generated by
<code><a rd-options="" href="/link/normalmix?package=ashr&version=2.0.5" data-mini-rdoc="ashr::normalmix">normalmix</a></code> or <code><a rd-options="" href="/link/unimix?package=ashr&version=2.0.5" data-mini-rdoc="ashr::unimix">unimix</a></code>.

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

dens function

A mixture of k components generated by
<code><a rd-options='' href='normalmix'>normalmix</a></code> or <code><a rd-options='' href='unimix'>unimix</a></code>.

dens: Find density at y, a generic function

Description

Usage

Arguments