split_scale-methods: Center and/or Scale Row-subsets of a Matrix or Matrix-like...

In bbuchsbaum/neuroim2: Data Structures and IO for Neuroimaging Data with an Emphasis on Functional Magnetic Resonance Imaging (FMRI)

Center and/or Scale Row-subsets of a Matrix or Matrix-like Object

Description

This function centers and/or scales the row-subsets of a numeric matrix or matrix-like object.

Implementation of split_scale for matrix objects. See split_scale for the generic definition and complete documentation.

Implementation of split_scale for matrix objects. See split_scale for the generic definition and complete documentation.

Implementation of split_scale for DenseNeuroVec objects. See split_scale for the generic definition and complete documentation.

Implementation of split_scale for DenseNeuroVec objects. See split_scale for the generic definition and complete documentation.

Implementation of split_scale for DenseNeuroVec objects. See split_scale for the generic definition and complete documentation.

Usage

split_scale(x, f, center, scale)

## S4 method for signature 'matrix,factor,logical,logical'
split_scale(x, f, center = TRUE, scale = TRUE)

## S4 method for signature 'matrix,factor,missing,missing'
split_scale(x, f)

## S4 method for signature 'DenseNeuroVec,factor,missing,missing'
split_scale(x, f)

## S4 method for signature 'DenseNeuroVec,factor,logical,missing'
split_scale(x, f, center)

## S4 method for signature 'DenseNeuroVec,factor,logical,logical'
split_scale(x, f, center, scale)

Arguments

x	A DenseNeuroVec object
f	Factor for grouping
center	Logical indicating whether to center
scale	Logical indicating whether to scale

Value

A new matrix or matrix-like object in which the original rows have been grouped by 'f' and then centered and/or scaled for each grouping.

Matrix of scaled values

Matrix of scaled values

Scaled DenseNeuroVec object

Scaled DenseNeuroVec object

Scaled DenseNeuroVec object

See Also

split_scale

split_scale

split_scale

split_scale

split_scale

Examples

M <- matrix(rnorm(1000), 10, 100)
fac <- factor(rep(1:2, each=5))
Ms <- split_scale(M, fac)

## Correctly centered
all(abs(apply(Ms[fac == 1,], 2, mean)) < .000001)
all(abs(apply(Ms[fac == 2,], 2, mean)) < .000001)

## Correctly scaled
all.equal(apply(Ms[fac == 1,], 2, sd), rep(1, ncol(Ms)))
all.equal(apply(Ms[fac == 2,], 2, sd), rep(1, ncol(Ms)))

bbuchsbaum/neuroim2 documentation built on Jan. 2, 2025, 3:38 p.m.