tmixture: Estimate Scale Factor in Mixture of t-Distributions
In richierocks/limma2: Linear Models for Microarray Data

Description Usage Arguments Details Value Author(s) See Also

This function estimates the unscaled standard deviation of the log fold change for differentially expressed genes. It is called by the function ebayes and is not intended to be called by users.

1 2	tmixture.vector(tstat,stdev.unscaled,df,proportion,v0.lim=NULL) tmixture.matrix(tstat,stdev.unscaled,df,proportion,v0.lim=NULL)

`tstat`	numeric vector or matrix of t-statistics
`stdev.unscaled`	numeric matrix conformal with `tstatf` containing the unscaled standard deviations for the coefficient estimators
`df`	numeric vector giving the degrees of freedom associated with `tstat`
`proportion`	assumed proportion of genes which are differentially expressed
`v0.lim`	numeric vector of length 2, assumed lower and upper limits for the estimated unscaled standard deviation

The values in each column of tstat are assumed to follow a mixture of an ordinary t-distribution, with mixing proportion 1-proportion, and (v0+v1)/v1 times a t-distribution, with mixing proportion proportion. Here v1=stdev.unscaled^2 and v0 is the value to be estimated.

Numeric vector of length equal to the number of columns of tstat and stdev.unscaled.

Gordon Smyth

ebayes

richierocks/limma2 documentation built on May 27, 2019, 8:47 a.m.