mvnrfish - Fisher information matrix for multivariate normal or least-squares regression

Data

NUMSAMPLES-by-NUMSERIES matrix with NUMSAMPLES samples of a NUMSERIES-dimensional random vector. If a data sample has missing values, represented as NaNs, the sample is ignored.

Design

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

• If NUMSERIES = 1, Design is a NUMSAMPLES-by-NUMPARAMS matrix with known values. This structure is the standard form for regression on a single series.

• If NUMSERIES ≥ 1, Design is a cell array. The cell array contains either one or NUMSAMPLES cells. Each cell contains a NUMSERIES-by-NUMPARAMS matrix of known values.

  If Design has a single cell, it is assumed to have the same Design matrix for each sample. If Design has more than one cell, each cell contains a Design matrix for each sample.

Covariance

NUMSERIES-by-NUMSERIES matrix of estimates for the covariance of the residuals of the regression.

MatrixFormat

(Optional) String that identifies parameters to be included in the Fisher information matrix:

• full - Default format. Compute the full Fisher information matrix for both model and covariance parameter estimates.

• paramonly - Compute only components of the Fisher information matrix associated with the model parameter estimates.

CovarFormat

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

• 'full' - Default method. The covariance matrix is a full matrix.

• 'diagonal' - The covariance matrix is a diagonal matrix.