Mixture decomposition via the simulated annealing algorithm
- 1 December 1991
- journal article
- Published by Wiley in Applied Stochastic Models and Data Analysis
- Vol. 7 (4) , 317-325
- https://doi.org/10.1002/asm.3150070403
Abstract
This paper presents the problem of the evaluation of the maximum likelihood estimator, when the likelihood function has multiple maxima, using the stochastic algorithm called ‘simulated annealing’. Analysis of the particular case of the decomposition of a mixture of five univariate normal distributions shows the properties of this methodology with respect to the E—M algorithm. The results are compared considering some distance measures between the estimated distribution functions and the true one.Keywords
This publication has 12 references indexed in Scilit:
- Cooling Schedules for Optimal AnnealingMathematics of Operations Research, 1988
- Simulated Annealing: Theory and ApplicationsPublished by Springer Nature ,1987
- Limit set of inhomogeneous Ornstein-Uhlenbeck processes, destabilization and annealingStochastic Processes and their Applications, 1986
- Diffusions for Global OptimizationSIAM Journal on Control and Optimization, 1986
- Convergence of an annealing algorithmMathematical Programming, 1986
- Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithmJournal of Optimization Theory and Applications, 1985
- A Monte carlo simulated annealing approach to optimization over continuous variablesJournal of Computational Physics, 1984
- Optimization by Simulated AnnealingScience, 1983
- Mixture Models, Outliers, and the EM AlgorithmTechnometrics, 1980
- Evaluation of the maximum-likelihood estimator where the likelihood equation has multiple rootsBiometrika, 1966