Maximum
likelihood estimation in a mixture regression model using the continuation
method
Authors
H. Hirose, Y. Komori
Source
IEICE Transactions A: on Fundamentals of Electronics,
Communications and Computer Sciences, Vol.E86A, No.5, pp.1256-1265
(2003.5)
Abstract
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.