mlmmmbd.em:
ML estimation under multivariate linear mixed models with block-diagonal covariance matrix and missing values
Description
Implementation of em.pan() that restricts the covariance matrix
for the random effects to be block-diagonal. This function
is identical to pan() in every way except that psi is now
characterized by a set of r matrices of dimension q x q.
Usage
mlmmmbd.em(y, subj, pred, xcol, zcol, start, maxits=100, eps=0.01)
Arguments
y
See description for mlmmm.em().
subj
See description for mlmmm.em().
pred
See description for mlmmm.em().
xcol
See description for mlmmm.em().
zcol
See description for mlmmm.em().
start
Same as for em.pan() except that the starting value for psi
have new dimensions: (q x q x r)
maxits
See description for mlmmm.em().
eps
See description for mlmmm.em(). Value
A list with the same components as that from em.pan(), with a
minor difference: the dimension of "psi" is now (q x q x r).
References
Schafer, J.L. and Yucel, R.M. (2002)
Computational strategies for multivariate linear mixed-effects
models with missing values, Journal of Computational and Graphical Statistics, 11, 421-442.