getV: Determine V-Matrix for a 'VCA' Object

In VCA: Variance Component Analysis

Determine V-Matrix for a 'VCA' Object

Description

Determine the estimated variance-covariance matrix of observations y.

Usage

getV(obj)

Arguments

obj	(VCA) object

Details

A linear mixed model can be written as y = Xb + Zg + e, where y is the column vector of observations, X and Z are design matrices assigning fixed (b), respectively, random (g) effects to observations, and e is the column vector of residual errors. The variance-covariance matrix of y is equal to Var(y) = ZGZ^{-T} + R, where R is the variance-covariance matrix of e and G is the variance-covariance matrix of g. Here, G is assumed to be a diagonal matrix, i.e. all random effects g are mutually independent (uncorrelated).

Value

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

Author(s)

Andre Schuetzenmeister [e-mail]

VCA documentation built on May 29, 2024, 1:48 a.m.