DocumentCode
2165106
Title
Global likelihood optimization via the cross-entropy method with an application to mixture models
Author
Botev, Zdravko ; Kroese, Dirk P.
Author_Institution
Dept. of Math., Queensland Univ., Brisbane, Qld., Australia
Volume
1
fYear
2004
fDate
5-8 Dec. 2004
Lastpage
535
Abstract
Global likelihood maximization is an important aspect of many statistical analyses. Often the likelihood function is highly multiextremal. This presents a significant challenge to standard search procedures, which often settle too quickly into an inferior local maximum. We present a new approach based on the cross-entropy (CE) method, and illustrate its use for the analysis of mixture models.
Keywords
convergence; maximum likelihood estimation; optimisation; search problems; cross-entropy method; global likelihood maximization; likelihood function; mixture models; optimization; statistical analyses; Constraint optimization; Convergence; Data analysis; Mathematical model; Mathematics; Optimization methods; Parameter estimation; Probability; Sampling methods; Statistical analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Simulation Conference, 2004. Proceedings of the 2004 Winter
Print_ISBN
0-7803-8786-4
Type
conf
DOI
10.1109/WSC.2004.1371358
Filename
1371358
Link To Document