tmixture {limma} | R Documentation

## Estimate Scale Factor in Mixture of t-Distributions

### Description

These functions estimate the unscaled standard deviation of the true (unobserved) log fold changes for differentially expressed genes. They are used by the functions `ebayes` and `eBayes` and are not intended to be called directly by users.

### Usage

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

### Arguments

`tstat` | numeric vector or matrix of t-statistics. `tmixture.vector` assumes a vector while `tmixture.matrix` assumes a matrix.
`stdev.unscaled` | numeric vector or matrix, conformal with `tstat`, containing the unscaled standard deviations of the coefficients used to compute the t-statistics.
`df` | numeric vector giving the degrees of freedom associated with `tstat`.
`proportion` | assumed proportion of genes that are differentially expressed.
`v0.lim` | numeric vector of length 2 giving the lower and upper limits for the estimated unscaled standard deviations.

### Details

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` is `stdev.unscaled^2` and `v0` is the value to be estimated.

### Value

Numeric vector, of length equal to the number of columns of `tstat`, containing estimated `v0` values.

### Author(s)

Gordon Smyth

### See Also

`eBayes`

[Package limma version 3.50.3 Index]