mlmmmbd.em: ML estimation under multivariate linear mixed models with...
In mlmmm: ML estimation under multivariate linear mixed models with missing values

Description Usage Arguments Value References

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.

1	mlmmmbd.em(y, subj, pred, xcol, zcol, start, maxits=100, eps=0.01)

`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().

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).

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.

mlmmm documentation built on May 1, 2019, 9:51 p.m.