morpFit#

Purpose#

Estimates a multivariate ordered response probit (MORP) model using flexible correlation structures and efficient maximum likelihood estimation.

result = morpFit(fname, dvordname, davordname, ivord[, ctl])#

Parameters:

fname (string) – Name of the dataset file to load.
dvordname (Kx1 string vector) – Vector of dependent ordinal variable names.
davordname (Kx1 string vector) – Vector of alternative availability variable names.
ivord (KxM string matrix) – Matrix of independent variable names for the ordered response.

ctl (struct) –

Optional. Instance of a morpControl structure for advanced control of estimation options. If not provided, defaults are used.

Member	Type	Default	Description
ctl.method	string	`"OVUS"`	Analytic approximation method to use in estimation.
ctl.spher	scalar	`0`	If 1, uses spherical parameterization; if 0, uses radial parameterization.
ctl.indep	scalar	`0`	If 1, assumes independence across equations; if 0, allows correlation.
ctl.indepfirst	scalar	`0`	If 1, estimates the independence model first before correlated estimation.
ctl.correst	matrix	`{}`	Correlation restriction matrix for advanced restriction specifications.

Returns:

result (scalar) – Returns 1 upon successful estimation.

Uses the morpControl structure to specify method, independence assumptions, spherical parameterizations, and correlation restrictions.
Automatically initializes and structures threshold parameters, independent variable parameters, and correlation parameters for the ordered response model.
Utilizes maxlik and maxprt for iterative maximum likelihood estimation with the appropriate likelihood gradient functions for initial estimation and final covariance computation.
Handles estimation for both independent and correlated structures, including advanced correlation restriction handling and scaling.

bhatlib

morpfit.src