residualize: Compute a regression model for each column in a matrix and...

In bbuchsbaum/neuroca: neuroca: multiblock component analysis for neuroimaging data

Compute a regression model for each column in a matrix and return residual matrix

Description

Compute a regression model for each column in a matrix and return residual matrix

Usage

residualize(form, X, design)

Arguments

form	the formula defining the model to fit for residuals
X	the response matrix
design	the data.frame containing the design variables specified in form argument.

Examples

X <- matrix(rnorm(20*10), 20, 10)
des <- data.frame(a=rep(letters[1:4], 5), b=factor(rep(1:5, each=4)))
xresid <- residualize(~ a+b, X, design=des)

## design is saturated, residuals should be zero
xresid2 <- residualize(~ a*b, X, design=des)
sum(xresid2) == 0

bbuchsbaum/neuroca documentation built on April 22, 2022, 2:50 a.m.