| getV {VCA} | R Documentation |
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 andre.schuetzenmeister@roche.com
[Package VCA version 1.5.1 Index]