orthonormalizeCovariates {ramwas} | R Documentation

## Orthonormalize Covariates

### Description

Takes a matrix of data frame with covariates, adds a constant covariate (optional), and orthonormalizes the set.

### Usage

    orthonormalizeCovariates(cvrt, modelhasconstant)

### Arguments

`cvrt` | A matrix or data frame with covariates (one column per covariate).
`modelhasconstant` | Set to `TRUE` to add a constant covariate into the set before normalization.

### Details

Factor variables are split into dummy variables before orthonormalization.
The operation is performed via QR decomposition (qr).

### Value

Returns a matrix with orthogonal columns with unit length, whose columns spans the same space as the covariates plus a constant (if `modelhasconstant` is `TRUE`).

### Note

This function is used in several parts of the pipeline.

### Author(s)

Andrey A Shabalin andrey.shabalin@gmail.com

### Examples

    # Sample matrix of covariates
    covariates = data.frame(a = 1:12, b = 12:1)

    # Orthonormalizing Covariates
    cvrtqr = orthonormalizeCovariates(covariates, modelhasconstant = TRUE)

    # Checking the results (round to ignore rounding errors)
    print( round(crossprod(cvrtqr),15) )

    # Stop if not orthonormal
    stopifnot(all.equal( crossprod(cvrtqr), diag(ncol(cvrtqr)) ))

    # Example with a factor variable
    groups = data.frame(gr = c("a","a","a","b","b","b","c","c","c"))
    orthonormalizeCovariates(groups)

[Package ramwas version 1.6.0 Index]