loglik.norm

Evaluates the observed-data loglikelihood function at a user-supplied
value of the parameter. This function is useful for monitoring the
progress of EM and data augmentation.

multivariate

An integrated set of functions for the analysis of
multivariate normal datasets with missing values, including implementation of
the EM algorithm, data augmentation, and multiple imputation.

John Fox

norm

Analysis of Multivariate Normal Datasets with Missing Values

loglik.norm function

<dl><dt>s</dt>
<dd>summary list of an incomplete normal data matrix created by the
function <code>prelim.norm</code>.</dd><dt>theta</dt>
<dd>vector of normal parameters expressed on transformed scale in packed
storage, such as one produced by the function <code>em.norm</code>.</dd>
</dl>

Arguments

Observed-data loglikelihood for normal data — loglik.norm

<dl>

<dt>s</dt>
<dd>summary list of an incomplete normal data matrix created by the
function <code>prelim.norm</code>.</dd>

<dt>theta</dt>
<dd>vector of normal parameters expressed on transformed scale in packed
storage, such as one produced by the function <code>em.norm</code>.</dd>
</dl>

loglik.norm: Observed-data loglikelihood for normal data

Description

Usage

Value

Arguments

References

See Also

Examples