R: Imputation of multivariate panel or cluster data

pan.bd {pan} | R Documentation

## Imputation of multivariate panel or cluster data

### Description

Implementation of 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

    pan.bd(y, subj, pred, xcol, zcol, prior, seed, iter=1, start)

### Arguments

`y` | See description for pan().
`subj` | See description for pan().
`pred` | See description for pan().
`xcol` | See description for pan().
`zcol` | See description for pan().
`prior` | Same as for pan() except that the hyperparameters for psi have new dimensions. The hyperparameter c is now a vector of length r, where c[j] contains the prior degrees of freedom for the jth block portion of psi (j=1,...,r). The hyperparameter Dinv is now an array of dimension c(q,q,r), where Dinv[,,j] contains the prior scale matrix for the jth block portion of psi (j=1,...,r).
`seed` | See description for pan().
`iter` | See description for pan().
`start` | See description for pan().

### Value

A list with the same components as that from pan(), with two minor differences: the dimension of "psi" is now (q x q x r x "iter"), and the dimension of "last\$psi" is now (q x q x r).

[Package pan version 1.6 Index]