mht (version 3.1.2)

data.scale: Scale a matrix

Description

Scale the data so each column has mean 0 and variance 1. This function is used as a pre-processing step to prep the data for analysis in all functions of the mht package.

Usage

data.scale(data,warning)

Arguments

data

Input matrix of dimension n * p; each row is an observation vector. The intercept should be included in the first column as (1,...,1). If not, it is added.

warning

Logical value. A warning message is printed if the intercept is added. Default is TRUE.

Value

data

Scaled data.

intercept

Logical value. TRUE if the intercept was already included in the input data.

means.data

Vector of means of the input data matrix.

sigma.data

Vector of variances of the input data matrix.

Details

Scale the data so each column has mean 0 and variance 1. If we note x a column of the output scaled matrix -except the first one which is the intercept, we have sum(x)=0 and sum(x^2)/n=1.

References

Multiple hypotheses testing for variable selection; F. Rohart 2011

Examples

## Not run: 
# x=matrix(rnorm(100*20),100,20)
# res=data.scale(x)
# x.scaled=res$data
# means.x=res$means.data
# sigma.x=res$sigma.data
# ## End(Not run)