cov_udi_single

data

<p>a vector of length R of "U","D" and "I"</p>

model

<p>This is an internal (non-exported) function. This help
  page provides additional documentation mainly intended for
  developers and expert users.</p>

internal

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

cov_udi_single function

Computes the covariance matrix for a single UDI model — cov_udi_single

Computes the covariance matrix for a single UDI model

cov_udi_single: Computes the covariance matrix for a single UDI model

Description

Usage

Arguments

Value