Results 291 to 300 of about 1,765,864 (313)

Markov Chain Robustness.

When a Markov chain models nature or social interactions, it is likely not followed exactly, but only approximately. We therefore introduce several notions of robustness for a Markov chain P. Our standard adversary can dynamically change transition probabilities of P by 1 ± ε, and our strong adversary can completely control each transition ...
openaire   +2 more sources

Analysis of a nonreversible Markov chain sampler

Annals of Applied Probability, 2000
Radford M Neal
exaly  

Ripple effect modelling of supplier disruption: integrated Markov chain and dynamic Bayesian network approach

International Journal of Production Research, 2020
Alexandre Dolgui, Dmitry Ivanov, Seyedmohsen Hosseini   +2 more
exaly  

Practical Markov Chain Monte Carlo

Statistical Science, 1992
Charles J Geyer
exaly  

Markov chains

2001
openaire   +1 more source

Regeneration in Markov Chain Samplers

Journal of the American Statistical Association, 1995
Luke Tierney, Per A Mykland
exaly  

Stability of a Markov-modulated Markov Chain, with Application to a Wireless Network Governed by two Protocols

Stochastic Systems, 2012
Seva Shneer, Sergey Foss
exaly  

Markov Chain Monte Carlo: Can We Trust the Third Significant Figure?

Statistical Science, 2008
James Flegal, Murali Haran
exaly  

Adaptive Markov Chain Monte Carlo through Regeneration

Journal of the American Statistical Association, 1998
Gareth Roberts, Sujit Sahu
exaly  

Assessing significance in a Markov chain without mixing

Proceedings of the National Academy of Sciences of the United States of America, 2017
Wesley Pegden, Alan Frieze, Maria Chikina   +2 more
exaly