sim_contrast1

nsamp

ncond

<p>the standard deviation of the errors</p>

err_sd

<p>Create simplest simulation, cj = mu 1 data used for contrast
analysis</p>

Implements the multivariate adaptive shrinkage (mash)
method of Urbut et al (2019) <DOI:10.1038/s41588-018-0268-8> for
estimating and testing large numbers of effects in many conditions
(or many outcomes). Mash takes an empirical Bayes approach to
testing and effect estimation; it estimates patterns of similarity
among conditions, then exploits these patterns to improve accuracy
of the effect estimates. The core linear algebra is implemented in
C++ for fast model fitting and posterior computation.

Peter Carbonetto

mashr

Multivariate Adaptive Shrinkage

Matthew Stephens

Sarah Urbut

Gao Wang

Yuxin Zou

Yunqi Yang

Sam Roweis

David Hogg

Jo Bovy

sim_contrast1 function

Create simplest simulation, cj = mu 1 data used for contrast
analysis — sim_contrast1

Create simplest simulation, cj = mu 1 data used for contrast
analysis

sim_contrast1: Create simplest simulation, cj = mu 1 data used for contrast analysis

Description

Usage

Arguments

Details

Examples