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Books on the topic 'Markov chain Monte Carlo'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

R, Gilks W., Richardson S, and Spiegelhalter D. J, eds. Markov chain Monte Carlo in practice. Chapman & Hall, 1996.

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2

R, Gilks W., Richardson S, and Spiegelhalter D. J, eds. Markov chain Monte Carlo in practice. Chapman & Hall, 1998.

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3

Liang, Faming, Chuanhai Liu, and Raymond J. Carroll. Advanced Markov Chain Monte Carlo Methods. John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470669723.

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4

S, Kendall W., Liang F. 1970-, and Wang J. S. 1960-, eds. Markov chain Monte Carlo: Innovations and applications. World Scientific, 2005.

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5

Liang, F. Advanced Markov chain Monte Carlo methods: Learning from past samples. Wiley, 2010.

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6

Joseph, Anosh. Markov Chain Monte Carlo Methods in Quantum Field Theories. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46044-0.

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7

Gamerman, Dani. Markov chain Monte Carlo: Stochastic simulation for Bayesian inference. Chapman & Hall, 1997.

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8

Freitas, Lopes Hedibert, ed. Markov chain Monte Carlo: Stochastic simulation for Bayesian inference. 2nd ed. Taylor & Francis, 2006.

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9

Roberts, Gareth O. Markov chain Monte Carlo: Some practical implications of theoretical results. University of Toronto, 1997.

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10

Cowles, Mary Kathryn. A simulation approach to convergence rates for Markov chain Monte Carlo algorithms. University of Toronto, Dept. of Statistics, 1996.

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11

Winkler, Gerhard. Image Analysis, Random Fields and Markov Chain Monte Carlo Methods. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-55760-6.

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12

Gerhard, Winkler. Image analysis, random fields and Markov chain Monte Carlo methods: A mathematical introduction. 2nd ed. Springer, 2003.

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13

Neal, Radford M. Markov chain Monte Carlo methods based on "slicing" the density function. University of Toronto, Dept. of Statistics, 1997.

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14

Brémaud, Pierre. Markov chains: Gibbs fields, Monte Carlo simulation, and queues. Springer, 1999.

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15

Suwa, Hidemaro. Geometrically Constructed Markov Chain Monte Carlo Study of Quantum Spin-phonon Complex Systems. Springer Japan, 2014. http://dx.doi.org/10.1007/978-4-431-54517-0.

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16

1946-, Winkler Gerhard, ed. Image analysis, random fields and Markov chain Monte Carlo methods: A mathematical introduction. 2nd ed. Springer, 2003.

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17

Margossian, Charles Christopher. Modernizing Markov Chains Monte Carlo for Scientific and Bayesian Modeling. [publisher not identified], 2022.

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18

Lunn, David Jonathan. The application of Markov chain Monte Carlo techniques to the study of population pharmacokinetics. University of Manchester, 1995.

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19

Nicol, David M. Automated parallelization of discrete state-space generation. Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 2000.

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20

Nicol, David M. Automated parallelization of discrete state-space generation. Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 2000.

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21

1947-, Gianola Daniel, ed. Likelihood, Bayesian and MCMC methods in quantitative genetics. Springer-Verlag, 2002.

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22

Mikhaĭlov, G. A. New Monte Carlo methods with estimating derivatives. VSP, 1995.

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23

Gamerman, Dani, and Hedibert F. Lopes. Markov Chain Monte Carlo. Chapman and Hall/CRC, 2006. http://dx.doi.org/10.1201/9781482296426.

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24

Handbook for Markov chain Monte Carlo. Taylor & Francis, 2011.

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25

Richardson, S., David Spiegelhalter, and W. R. Gilks. Markov Chain Monte Carlo in Practice. Taylor & Francis Group, 1995.

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26

Richardson, S., David Spiegelhalter, and W. R. Gilks. Markov Chain Monte Carlo in Practice. Taylor & Francis Group, 1995.

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27

Carroll, Raymond, Faming Liang, and Chuanhai Liu. Advanced Markov Chain Monte Carlo Methods. Wiley & Sons, Incorporated, John, 2010.

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28

Brooks, Steve, Andrew Gelman, Galin Jones, and Xiao-Li Meng, eds. Handbook of Markov Chain Monte Carlo. Chapman and Hall/CRC, 2011. http://dx.doi.org/10.1201/b10905.

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29

Gilks, W. R., S. Richardson, and David Spiegelhalter, eds. Markov Chain Monte Carlo in Practice. Chapman and Hall/CRC, 1995. http://dx.doi.org/10.1201/b14835.

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30

Brooks, Steve, Andrew Gelman, Xiao-Li Meng, and Galin L. Jones. Handbook of Markov Chain Monte Carlo. Taylor & Francis Group, 2011.

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31

Plehn, Thomas. McMc-Methoden - Markov Chain Monte Carlo. GRIN Verlag GmbH, 2009.

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32

Brooks, Steve, Andrew Gelman, Xiao-Li Meng, and Galin Jones. Handbook of Markov Chain Monte Carlo. Taylor & Francis Group, 2011.

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33

Brooks, Steve, Andrew Gelman, Xiao-Li Meng, and Galin Jones. Handbook of Markov Chain Monte Carlo. Taylor & Francis Group, 2011.

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34

Kamatani, Kengo. Stability of Markov Chain Monte Carlo Methods. Springer Japan, 2023.

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35

Markov chain Monte Carlo: Innovations and applications. World Scientific, 2006.

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36

Coolen, A. C. C., A. Annibale, and E. S. Roberts. Markov Chain Monte Carlo sampling of graphs. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0006.

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Abstract:

This chapter looks at Markov Chain Monte Carlo techniques to generate hard- and soft-constrained exponential random graph ensembles. The essence is to define a Markov chain based on ergodic randomization moves acting on a network with transition probabilities which satisfy detailed balance. This is sufficient to ensure that the Markov chain will sample from the ensemble with the desired probabilities. This chapter studies several commonly seen randomization move sets and carefully defines acceptance probabilities for a range of different ensembles using both the Metropolis–Hastings and the Gla

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37

Liang, F. Markov Chain Monte Carlo: Innovations and Applications. World Scientific Publishing Co Pte Ltd, 2005.

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38

Liang, F. Markov Chain Monte Carlo: Innovations and Applications. World Scientific Publishing Co Pte Ltd, 2005.

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39

Markov Chain Monte Carlo in Practice (Interdisciplinary Statistics). Chapman & Hall/CRC, 1995.

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40

Jones, Galin L. Convergence rates and Monte Carlo standard errors for Markov chain Monte Carlo Algorithms. 2001.

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41

Tweedie, Richard L., and Gareth O. Roberts. Understanding Monte Carlo Markov Chain (Springer Series in Statistics). Springer, 2008.

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42

Markov chain Monte Carlo: Stochastic simulation for Bayesian inference. Chapman & Hall, 1997.

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43

Plehn, Thomas. Markov Chain Monte Carlo - Methoden: Herleitung, Beweis und Implementierung. Bachelor + Master Publishing, 2014.

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44

Carroll, Raymond, Faming Liang, and Chuanhai Liu. Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples. Wiley & Sons, Incorporated, John, 2011.

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45

Carroll, Raymond, Faming Liang, and Chuanhai Liu. Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples. Wiley & Sons, Incorporated, John, 2011.

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46

Carroll, Raymond, Faming Liang, and Chuanhai Liu. Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples. Wiley & Sons, Limited, John, 2010.

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47

Carroll, Raymond, Faming Liang, and Chuanhai Liu. Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples. Wiley & Sons, Incorporated, John, 2010.

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48

Markov Chains Analytic And Monte Carlo Computations. John Wiley & Sons Australia Ltd, 2014.

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49

Geometrically Constructed Markov Chain Monte Carlo Study of Quantum Spinphonon Complex Systems Springer Theses. Springer Verlag, Japan, 2013.

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50

Graham, Carl. Markov Chains: Analytic and Monte Carlo Computations. Wiley & Sons, Incorporated, John, 2014.

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