A GENERAL PROCEDURE FOR OBTAINING MAXIMUM LIKELIHOOD ESTIMATES IN GENERALIZED REGRESSION MODEL.

Authors :: Oberhofer, W.
Kmenta, J.
Source :: Econometrica; May74, Vol. 42 Issue 3, p579-590, 12p
Publication Year :: 1974
Abstract: This paper describes an iterative procedure for obtaining maximum likelihood estimates of the parameters of a generalized regression model when direct maximization with respect to all parameters is difficult. A proof of convergence and some interesting applications are provided. [ABSTRACT FROM AUTHOR]

Subjects :: REGRESSION analysis
MATHEMATICAL statistics
STATISTICS
ANALYSIS of variance
STATISTICAL correlation
MULTIVARIATE analysis
AUTOREGRESSION (Statistics)
ESTIMATION theory
LEAST squares

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