Loglikelihood function for multivariate normal regression with missing data
Objective = ecmmvnrobj(Data, Design, Parameters, Covariance,
CovarFormat)


 A matrix or a cell array that handles two model structures:





 (Optional) String that specifies the format for the covariance matrix. The choices are:

Objective = ecmmvnrobj(Data, Design, Parameters, Covariance,
CovarFormat)
computes a loglikelihood function based on
current maximum likelihood parameter estimates with missing data. Objective
is
a scalar that contains the leastsquares objective function.
You can configure Design
as a matrix if NUMSERIES
= 1
or as a cell array if NUMSERIES
≥ 1
.
If Design
is a cell array and NUMSERIES
=
1, each cell contains a NUMPARAMS
row
vector.
If Design
is a cell array and NUMSERIES
> 1, each cell contains a NUMSERIES
byNUMPARAMS
matrix.
See Multivariate Normal Regression, LeastSquares Regression, CovarianceWeighted Least Squares, Feasible Generalized Least Squares, and Seemingly Unrelated Regression.
ecmmvnrmle
 mvnrmle
 mvnrobj