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 in linear mixed models is implemented, following
             Searle et al. 1991 (ANOVA for unbalanced data). For better performance the SWEEP-Operator is now implemented
             for generating the ANOVA Type-1 error sum of squares. The primary objective of this package is to perform
             Variance Component Analyses (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 and for individual variance components is
             implemented. These are used in the Chi-Squared tests against a claimed value, and in the respective confidence intervals. 
             Satterthwaite's approximation of denominator degrees of freedom in t-/F-tests of fixed effects are also
             available. 
             There are several functions for extracting, random effects, fixed effects, variance-covariance
             matrices of random and fixed effects. Residuals (marginal, conditional) can be extracted as raw, standardized
             and studentized residuals.
             Additionally, plotting methods for residuals and random effects and a variability chart are available. The latter
             is useful for visualizing the variability in sub-classes emerging from the experimental design.

MPinv: Moore-Penrose Inverse of a Matrix.

Description

Usage

Arguments

Value