| loadings_mmes | R Documentation |
Reconstructs the normalized loadings matrix and specific variances of a
fam() or rrm() covariance-shaping factor fitted inside
vsm(), on the same scale as the fitted covariance matrix returned in
object$theta.
loadings_mmes(object, term = NULL, varianceScale=TRUE, rotation=TRUE)
object |
a fitted model of class |
term |
character name of the random term (matching a name in
|
varianceScale |
Whether to return loadings multiplied by
|
rotation |
a logical value to indicate if loadings should be rotated by its singular vectors. |
fam()/rrm() remove their otherwise redundant internal scale so
that vsm() owns the single overall variance; the loadings and specific
variances reported by loadings_mmes are re-normalized so that
\Sigma = \sigma^2(\Lambda\Lambda^{\mathsf T}+\Psi)
reproduces object$theta[[term]] exactly when
varianceScale=FALSE, where \sigma^2 is
object$covPar[[term]][1]. With varianceScale=TRUE, the
returned loadings crossproduct plus the diagonal of the returned specific
variances directly reproduces that covariance.
A list containing:
a levels-by-factor matrix \Lambda.
a named vector of specific variances \Psi (identically
zero for every level in a rrm() term).
the fitted overall variance scale.
"fa" or "rr".
the resolved term name.
scores_mmes, fam, rrm, vsm, mmes.
## Not run:
mix <- mmes(BLUEs ~ trial,
random = ~ vsm(fam(trial, 2), ism(genotype)),
rcov = ~ units, data = dt)
loadings_mmes(mix)
## End(Not run)
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