Learn R Programming

mlmmm (version 0.3-1.2)

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.