- Stationarity and Convergence of the Metropolis-Hastings Algorithm: Insights into Theoretical Aspects
2019/01/17 by S.D. Hill, James C. Spall · 1 citation
Mathematics · Computer Science · Engineering · #Markov Chains and Monte Carlo Methods #Bayesian Methods and Mixture Models #Gaussian Processes and Bayesian Inference #Markov chain Monte Carlo #Metropolis–Hastings algorithm #Gibbs sampling #Algorithm #Computer science #Monte Carlo method #Convergence (economics) #Markov chain #Sampling (signal processing) #Sequence (biology) #Markov process #Rejection sampling #Range (aeronautics) #Probability distribution #Hybrid Monte Carlo #Mathematics #Mathematical optimization #Artificial intelligence #Statistics #Machine learning #Bayesian probability #Engineering
- Estimation via Markov chain Monte Carlo
2003/03/26 by James C. Spall · 2 citations
Mathematics · Computer Science · #Markov Chains and Monte Carlo Methods #Bayesian Methods and Mixture Models #Statistical Methods and Bayesian Inference #Markov chain Monte Carlo #Gibbs sampling #Metropolis–Hastings algorithm #Computer science #Markov chain #Rejection sampling #Monte Carlo method #Hybrid Monte Carlo #Algorithm #Mathematics #Statistics #Artificial intelligence #Machine learning #Bayesian probability
- The Multiple-Try Method and Local Optimization in Metropolis Sampling
2000/03/01 by Jun S. Liu, Faming Liang, Wing Hung Wong · 1 citation
Mathematics · Computer Science · Physics and Astronomy · #Markov Chains and Monte Carlo Methods #Bayesian Methods and Mixture Models #Scientific Research and Discoveries #Metropolis–Hastings algorithm #Markov chain Monte Carlo #Gibbs sampling #Markov chain #Sampling (signal processing) #Rejection sampling #Computer science #Monte Carlo method #Random walk #Algorithm #Mathematical optimization #Mathematics #Hybrid Monte Carlo #Statistics #Artificial intelligence #Machine learning #Bayesian probability