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Maximum Likelihood Estimation in a Mixture Regression Model Using the Continuation Method
Hideo HIROSE Yoshio KOMORI
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2003/05/01
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Numerical Analysis and Optimization
Newton-Raphson, simplex method, power-law, Weibull distribution, Weibull-power-law,
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To an extremely difficult problem of finding the maximum likelihood estimates in a specific mixture regression model, a combination of several optimization techniques is found to be useful. These algorithms are the continuation method, Newton-Raphson method, and simplex method. The simplex method searches for an approximate solution in a wider range of the parameter space, then a combination of the continuation method and the Newton-Raphson method finds a more accurate solution. In this paper, this combination method is applied to find the maximum likelihood estimates in a Weibull-power-law type regression model.