squeezeMVar {betr}R Documentation

Smooth sample covariance matrices

Description

An internal function to smooth a set of sample covariance matrices by computing empirical Bayes posterior means.

Usage

squeezeMVar(S, df, Lambda = NULL, nu = NULL)

Arguments

S a list of covariance matrices
df numeric vector of degrees of freedom for covariance matrices
Lambda use this target covariance matrix instead of calculating it from the data
nu use this nu instead of calculating it from the data

Details

Calculate shrinkage estimates for covariance matrices using the procedure of Tai and Speed (2006) and Smyth (2004)

Value

varPost list of posterior covariance matrices
varPrior target covariance matrix
dfPrior prior degrees of freedom

Author(s)

Martin Aryee

References

Smyth, G. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Statistical applications in genetics and molecular biology (2004) vol. 3

Tai, Y and Speed, T. A multivariate empirical Bayes statistic for replicated microarray time course data. Annals of Statistics (2006) vol. 34 (5) pp. 2387-2412

See Also

betr


[Package betr version 1.0.0 Index]