formXtViX | R Documentation |
This is a service routine for gamm
. Given,
V
, an estimated covariance matrix obtained using extract.lme.cov2
this
routine forms a matrix square root of X^TV^{-1}X
as efficiently as possible, given
the structure of V
(usually sparse).
formXtViX(V,X)
V |
A data covariance matrix list returned from |
X |
A model matrix. |
The covariance matrix returned by extract.lme.cov2
may
be in a packed and re-ordered format, since it is usually sparse. Hence a
special service routine is required to form the required products involving
this matrix.
A matrix, R such that crossprod(R)
gives X^TV^{-1}X
.
Simon N. Wood simon.wood@r-project.org
For lme
see:
Pinheiro J.C. and Bates, D.M. (2000) Mixed effects Models in S and S-PLUS. Springer
For details of how GAMMs are set up for estimation using lme
see:
Wood, S.N. (2006) Low rank scale invariant tensor product smooths for Generalized Additive Mixed Models. Biometrics 62(4):1025-1036
https://www.maths.ed.ac.uk/~swood34/
gamm
, extract.lme.cov2
require(mgcv)
library(nlme)
data(ergoStool)
b <- lme(effort ~ Type, data=ergoStool, random=~1|Subject)
V1 <- extract.lme.cov(b, ergoStool)
V2 <- extract.lme.cov2(b, ergoStool)
X <- model.matrix(b, data=ergoStool)
crossprod(formXtViX(V2, X))
t(X)
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