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|Title:||Real-Parameter Evolutionary Monte Carlo with Applications to Bayesian Mixture Models||Authors:||Liang, F.
Evolutionary Monte Carlo
Markov chain Monte Carlo
|Issue Date:||Jun-2001||Citation:||Liang, F.,Wong, W.H. (2001-06). Real-Parameter Evolutionary Monte Carlo with Applications to Bayesian Mixture Models. Journal of the American Statistical Association 96 (454) : 653-666. ScholarBank@NUS Repository.||Abstract:||We propose an evolutionary Monte Carlo algorithm to sample from a target distribution with real-valued parameters. The attractive features of the algorithm include the ability to learn from the samples obtained in previous steps and the ability to improve the mixing of a system by sampling along a temperature ladder. The effectiveness of the algorithm is examined through three multimodal examples and Bayesian neural networks. The numerical results confirm that the real-coded evolutionary algorithm is a promising general approach for simulation and optimization.||Source Title:||Journal of the American Statistical Association||URI:||http://scholarbank.nus.edu.sg/handle/10635/105324||ISSN:||01621459|
|Appears in Collections:||Staff Publications|
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