logLik.lm.rrpp: Calculate the log-likelihood of a lm.rrpp fit

In RRPP: Linear Model Evaluation with Randomized Residuals in a Permutation Procedure

Calculate the log-likelihood of a lm.rrpp fit

Description

logLik.lm.rrpp returns the log-likelihood of an lm.rrpp object. Ridge regularization will be performed for ill-conditioned or singular residual covariance matrices, but dimension reduction could be augmented via projection, using the arguments, tol and pc.no. See ordinate for details.

Usage

## S3 method for class 'lm.rrpp'
logLik(object, tol = NULL, pc.no = NULL, Z = TRUE, gls.null = FALSE, ...)

Arguments

object	Object from lm.rrpp
tol	A value indicating the magnitude below which components should be omitted, following projection. See ordinate for details.
pc.no	Optionally, a number specifying the maximal number of principal components, passed onto ordinate, as argument, rank.
Z	A logical value for whether to calculate Z scores based on RRPP.
gls.null	A logical value for if a fit has a GLS estimation, should the null model (intercept) also have a GLS estimation, for estimating Z. Should be FALSE if the log-likelihood is measured to compare different GLS estimations for a covariance matrices
...	further arguments passed to or from other methods

Author(s)

Michael Collyer

RRPP documentation built on Aug. 16, 2023, 1:06 a.m.