meanmat.hat {HDTD} | R Documentation

## Estimation the Mean Matrix

### Description

This function estimates the mean matrix.

### Usage

    meanmat.hat(datamat, N, group.sizes = NULL, group.vars = NULL)

### Arguments

`datamat` | numeric matrix containing the transposable data.
`N` | positive integer number indicating the sample size, i.e., the number of subjects.
`group.sizes` | numeric vector indicating the size of the row or column groups that share the same mean vector. It should be used only when `group.vars=`'`rows`' or '`columns`'.
`group.vars` | character indicating that the mean matrix can be simplified over the row or column variables. Options include '`rows`' or '`columns`'.

### Details

It is assumed that there are `nrow(datamat)` row variables and `ncol(datamat)`/`N` column variables in `datamat`. Further, `datamat` should be written in such a way that every `ncol(datamat)`/`N` consecutive columns belong to the same subject and the order of the column variables in each block is preserved across subjects.

### Value

Returns a list with components:

`estmeanmat` | the estimated mean matrix.
`N` | the sample size.
`n.rows` | the number of row variables.
`n.cols` | the number of column variables.

### Author(s)

Anestis Touloumis

### References

Touloumis, A., Marioni, J. C. and Tavare, S. (2016) HDTD: Analyzing multi-tissue gene expression data. Bioinformatics 32, 2193–2195.

### Examples

    data(VEGFmouse)
    ## The sample mean matrix of the VEGF mouse data.
    sample_mean <- meanmat.hat(datamat = VEGFmouse, N = 40)
    sample_mean
    sample_mean$estmeanmat

[Package HDTD version 1.26.0 Index]