getV {VCA}R Documentation

Determine V-Matrix for a 'VCA' Object

Description

Determine the estimated variance-covariance matrix of observations yy.

Usage

getV(obj)

Arguments

obj

(VCA) object

Details

A linear mixed model can be written as y=Xb+Zg+ey = Xb + Zg + e, where yy is the column vector of observations, XX and ZZ are design matrices assigning fixed (bb), respectively, random (gg) effects to observations, and ee is the column vector of residual errors. The variance-covariance matrix of yy is equal to Var(y)=ZGZT+RVar(y) = ZGZ^{-T} + R, where RR is the variance-covariance matrix of ee and GG is the variance-covariance matrix of gg. Here, GG is assumed to be a diagonal matrix, i.e. all random effects gg are mutually independent (uncorrelated).

Value

(VCA) object with additional elements in the 'Matrices' element, including matrix VV.

Author(s)

Andre Schuetzenmeister andre.schuetzenmeister@roche.com


[Package VCA version 1.5.1 Index]