DCrr {quantiseqr} | R Documentation

## Perform robust regression

### Description

Perform robust regression

### Usage

    DCrr(b, A, method = c("hampel", "huber", "bisquare"), scaling = NULL)

### Arguments

`b` | Numeric vector containing the right-hand side of the quadratic function to be minimized.
`A` | Numeric matrix containing the coefficients of the quadratic function to be minimized.
`method` | Character specifying the robust regression method to be used among deconvolution methods: "hampel", "huber", or "bisquare". Default: "hampel".
`scaling` | A vector of scaling factors to by applied to the estimates. Its length should equal the number of columns of A.

### Details

The `MASS::rlm()` function is used as underlying framework. Please refer to that function for more details.

### Value

A vector containing robust least-square estimates.

### Examples

    data(dataset_racle)
    mixture <- dataset_racle$expr_mat
    signature.file <- system.file(
      "extdata", "TIL10_signature.txt", package = "quantiseqr", mustWork = TRUE)
    signature <- read.table(signature.file, header = TRUE, sep = "\t", row.names = 1)
    scaling.file <- system.file(
      "extdata", "TIL10_mRNA_scaling.txt", package = "quantiseqr", mustWork = TRUE)
    scaling <- as.vector(
      as.matrix(read.table(scaling.file, header = FALSE, sep = "\t", row.names = 1)))

    cgenes <- intersect(rownames(signature), rownames(mixture))
    b <- as.vector(as.matrix(mixture[cgenes,1, drop=FALSE]))
    A <- as.matrix(signature[cgenes,])

    # cellfrac <- quantiseqr:::DCrr(b = b, A = A, scaling = scaling)

[Package quantiseqr version 1.2.0 Index]