ecmmvnrobj
Log-likelihood function for multivariate normal regression with missing data
Syntax
Objective = ecmmvnrobj(Data,Design,Parameters,Covariance,CovarFormat)
Arguments
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| A matrix or a cell array that handles two model structures:
|
|
|
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| (Optional) Character vector that specifies the format for the covariance matrix. The choices are:
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Description
Objective = ecmmvnrobj(Data,Design,Parameters,Covariance,CovarFormat)
computes
a log-likelihood function based on current maximum likelihood parameter
estimates with missing data. Objective
is a scalar
that contains the least-squares objective function.
Notes
You can configure Design
as a matrix if NUMSERIES
= 1
or as a cell array if NUMSERIES
≥ 1
.
If
Design
is a cell array andNUMSERIES
=1
, each cell contains aNUMPARAMS
row vector.If
Design
is a cell array andNUMSERIES
>1
, each cell contains aNUMSERIES
-by-NUMPARAMS
matrix.
Examples
See Multivariate Normal Regression, Least-Squares Regression, Covariance-Weighted Least Squares, Feasible Generalized Least Squares, and Seemingly Unrelated Regression.