MPinv

(object) two-dimensional, for which a
  Moore-Penrose inverse has to be computed

(numeric) tolerance value to be used in
  comparisons

This function is originally defined in package 'MASS'. It
was adapted to be able to deal with matrices from the
'Matrix' package, e.g. sparse matrices.

ANOVA-type estimation (prediction) of random effects and variance components in linear mixed models,
    is implemented. Random models, a sub-set of mixed models, can be fit applying a Variance Component Analysis (VCA).
    This is a special type of analysis frequently used in verifying the precision performance of diagnostics. 
    The Satterthwaite approximation of the total degrees of freedom is implemented. There are several functions 
    for extracting, random effects, fixed effects, variance-covariance matrices of random and fixed effects. 
    Residuals can be extracted as raw, standardized and studentized residuals. Additionally, a variability chart 
    is implemented for visualizing the variability in sub-classes emerging from an experimental design ('varPlot').

MPinv: Moore-Penrose Inverse of a Matrix.

Description

Usage

Arguments

Value