Results 271 to 280 of about 221,738 (314)

Markov Chain Monte Carlo

2010
The Markov chain Monte Carlo (MCMC) revolution sweeping statistics is drastically changing how statisticians perform integration and summation. In particular, the Metropolis algorithm and Gibbs sampling make it straightforward to construct a Markov chain that samples from a complicated conditional distribution.
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Monte Carlo / Monte Carlo Markov Chain

2014
The Monte Carlo simulation is a versatile method for analyzing the behavior of some activities, plans or processes that involve uncertainty. The method was invented by scientists working on the atomic bomb in the 1940s. It uses randomness to obtain random variable estimates, similarly to the gambling process.
Castellano R., CEDROLA, ELENA
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Markov chain Monte Carlo

Resonance, 2002
Daniel Sorensen, Daniel Gianola
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Monte Carlo Markov Chains

2016
Monte Carlo Markov Chains (MCMC) are a powerful method to analyze scientific data that has become popular with the availability of modern-day computing resources. The basic idea behind an MCMC is to determine the probability distribution function of quantities of interest, such as model parameters, by repeatedly querying datasets used for their ...
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Monte Carlo Markov Chains

2020
can be used if one is able to compute the integral analytically, which is seldom the case.
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Markov Chain Monte Carlo Method

2023
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Stochastic Gradient Markov Chain Monte Carlo

Journal of the American Statistical Association, 2021
Christopher John Nemeth, Paul Fearnhead
exaly  

Markov Chain Monte Carlo

2022
Swathi Padmanabhan, Uma Ranjan
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Convergence Diagnostics for Markov Chain Monte Carlo

Annual Review of Statistics and Its Application, 2020
Vivekananda Roy
exaly  

Markov-Chain Monte Carlo

2018
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