ecmmvnrfish
Fisher information matrix for multivariate normal regression model
Syntax
Fisher = ecmmvnrfish(Data,Design,Covariance,Method,MatrixFormat,CovarFormat)
Arguments
|
|
| A matrix or a cell array that handles two model structures:
|
|
|
| (Optional) Character vector that identifies method of calculation for the information matrix:
|
| (Optional) Character vector that identifies parameters to be included in the Fisher information matrix:
|
| (Optional) Character vector that specifies the format for the covariance matrix. The choices are:
|
Description
Fisher = ecmmvnrfish(Data,Design,Covariance,Method,MatrixFormat,CovarFormat)
computes
a Fisher information matrix based on current maximum likelihood or
least-squares parameter estimates that account for missing data.
Fisher
is a NUMPARAMS
-by-NUMPARAMS
Fisher
information matrix or Hessian matrix. The size of NUMPARAMS
depends
on MatrixFormat
and on current parameter estimates.
If MatrixFormat = 'full'
,
NUMPARAMS = NUMSERIES * (NUMSERIES + 3)/2
If MatrixFormat = 'paramonly'
,
NUMPARAMS = NUMSERIES
Note
ecmmvnrfish
operates slowly if you calculate the full Fisher
information matrix.
Examples
See Multivariate Normal Regression, Least-Squares Regression, Covariance-Weighted Least Squares, Feasible Generalized Least Squares, and Seemingly Unrelated Regression.
Version History
Introduced in R2006a