Description Usage Arguments Value
A pure R
implementation of the penalized least
squares (PLS) approach for computing linear mixed model
deviances. The purpose is to clarify how PLS works without
having to read through C++ code, and as a sandbox for
trying out modifications to PLS.
1 2 |
X |
fixed effects model matrix |
y |
response |
Zt |
transpose of the sparse model matrix for the random effects |
Lambdat |
upper triangular sparse Cholesky factor of the relative covariance matrix of the random effects |
thfun |
a function that takes a value of
|
weights |
prior weights |
offset |
offset |
REML |
calculate REML deviance? |
... |
additional arguments |
a function that evaluates the deviance or REML criterion
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