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检索条件"主题词=Metropolis-Hastings algorithms"
16 条 记 录,以下是1-10 订阅
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ON THE ACCEPT-REJECT MECHANISM FOR metropolis-hastings algorithms
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ANNALS OF APPLIED PROBABILITY 2023年 第6B期33卷 5279-5333页
作者: Glatt-holtz, Nathan Krometis, Justin Mondaini, Cecilia Tulane Univ Dept Math New Orleans LA 70118 USA Virginia Tech Natl Secur Inst Blacksburg VA USA Virginia Tech Dept Math Blacksburg VA USA Drexel Univ Dept Math Philadelphia PA USA
This work develops a powerful and versatile framework for determin-ing acceptance ratios in metropolis-hastings-type Markov kernels widely used in statistical sampling problems. Our approach allows us to derive new cl... 详细信息
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Probit and Logit Model Selection
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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2011年 第1期40卷 159-175页
作者: Chen, Guo Tsurumi, Hiroki Rutgers State Univ Dept Econ New Brunswick NJ 08901 USA
Monte Carlo experiments are conducted to compare the Bayesian and sample theory model selection criteria in choosing the univariate probit and logit models. We use five criteria: the deviance information criterion (DI... 详细信息
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An Efficient Sampling Algorithm for Non-smooth Composite Potentials
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JOURNAL OF MACHINE LEARNING RESEARCH 2022年 第1期23卷 1-50页
作者: Mou, Wenlong Flammarion, Nicolas Wainwright, Martin J. Bartlett, Peter L. Univ Calif Berkeley Dept EECS Berkeley CA 94720 USA Ecole Polytech Fed Lausanne Sch Comp & Commun Sci CH-1015 Lausanne Switzerland Univ Calif Berkeley Dept Stat Berkeley CA 94720 USA
We consider the problem of sampling from a density of the form p(x) ? exp(-f (x) - g(x)), where f : Rd-+ R is a smooth function and g : R-d-+ R is a convex and Lipschitz function. We propose a new algorithm based on t... 详细信息
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Weak convergence and optimal tuning of the reversible jump algorithm
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MATHEMATICS AND COMPUTERS IN SIMULATION 2019年 161卷 32-51页
作者: Gagnon, Philippe Bedard, Mylene Desgagne, Alain Univ Oxford Dept Stat 24-29 St Giles Oxford OX1 3LB England Univ Montreal Dept Math & Stat CP 6128Succursale Ctr Ville Montreal PQ H3C 3J7 Canada Univ Quebec Montreal Dept Math CP 8888Succursale Ctr Ville Montreal PQ H3C 3P8 Canada
The reversible jump algorithm is a useful Markov chain Monte Carlo method introduced by Green (1995) that allows switches between subspaces of differing dimensionality, and therefore, model selection. Although this me... 详细信息
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A computable bound of the essential spectral radius of finite range metropolis-hastings kernels
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STATISTICS & PROBABILITY LETTERS 2016年 117卷 72-79页
作者: Herve, Loic Ledoux, James INSA Rennes IRMAR F-35042 Rennes France CNRS UMR 6625 F-35708 Rennes France Univ Bretagne Loire Rennes France
Let pi be a positive continuous target density on R. Let P be the metropolis-hastings operator on the Lebesgue space L-2 (pi) corresponding to a proposal Markov kernel Q on R. When using the quasi-compactness method t... 详细信息
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Markov chain Monte Carlo for dynamic generalised linear models
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BIOMETRIKA 1998年 第1期85卷 215-227页
作者: Gamerman, D Univ Fed Rio de Janeiro Inst Matemat BR-21945970 Rio De Janeiro Brazil
This paper presents a new methodological approach for carrying out Bayesian inference about dynamic models for exponential-family observations. The approach is;simulation-based and involves the use of Markov chain Mon... 详细信息
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Phylogenetic inference for binary data on dendograms using Markov chain Monte Carlo
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JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS 1997年 第1期6卷 122-131页
作者: Mau, B Newton, MA UNIV WISCONSIN DEPT STATMADISONWI 53706 UNIV WISCONSIN DEPT BIOSTATMADISONWI 53706
Using a stochastic model for the evolution of discrete characters among a group of organisms, we derive a Markov chain that simulates a Bayesian posterior distribution on the space of dendograms. A transformation of t... 详细信息
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The ODE method for stability of skip-free Markov chains with applications to MCMC
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ANNALS OF APPLIED PROBABILITY 2008年 第2期18卷 664-707页
作者: Fort, Gersende Meyn, Sean Moulines, Eric Priouret, Pierre Telecom Paris CNRS Lab Traitement & Commun & Informat F-75634 Paris 13 France Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA Univ Illinois Coordinated Sci Lab Urbana IL 61801 USA Univ Paris 06 Lab Probabil & Modeles Aleatoires F-75252 Paris 05 France
In this paper, some of these techniques are extended to a general class of skip-free Markov chains. As in the case of queueing models, a fluid approximation is obtained by scaling time, space and the initial condition... 详细信息
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An adaptive version for the metropolis Adjusted Langevin algorithm with a truncated drift
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METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY 2006年 第2期8卷 235-254页
作者: Atchade, Yves F. Univ Ottawa Dept Math & Stat Ottawa ON K1N 6N5 Canada
This paper extends some adaptive schemes that have been developed for the Random Walk metropolis algorithm to more general versions of the metropolis-hastings (MH) algorithm, particularly to the metropolis Adjusted La... 详细信息
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On the Flexibility of metropolis-hastings Acceptance Probabilities in Auxiliary Variable Proposal Generation
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SCANDINAVIAN JOURNAL OF STATISTICS 2011年 第2期38卷 342-358页
作者: Storvik, Geir Univ Oslo Dept Math N-0316 Oslo Norway
Use of auxiliary variables for generating proposal variables within a metropolis-hastings setting has been suggested in many different settings. This has in particular been of interest for simulation from complex dist... 详细信息
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