The Equivalence of Generalized Least Squares and Maximum Likelihood Estimates in the Exponential Family
A. CharnesCenter for Cybernetic Studies , University of Texas at Austin , Austin , Tex. , 78712 , USAE. L. Fromestatistics-operations research , University of Texas at Austin , Austin , Tex. , 78712 , USAPing Yustatistics-operations research , University of Texas at Austin , Austin , Tex. , 78712 , USA
1976en
ABI
Abstract
Abstract The method of iterative weighted least squares can be used to estimate the parameters in a nonlinear regression model. If the dependent variables are observations from a member of the regular exponential family, then under mild conditions it is shown that the IWLS estimates are identical to those obtained using the maximum likelihood principle. An application is provided to illustrate the results.
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