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Editorial: Special issue on adaptive Monte Carlo methods

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References

  • Andrieu, C., Thoms, J.: An overview of controlled MCMC. Stat. Comput. 18 (2008)

  • Cai, B., Meyer, R., Perron, F.: Metropolis Hastings algorithms with adaptive proposals. Stat. Comput. 18 (2008). doi:10.1007/s11222-008-9051-5

  • Cappe, O., Guillin, A., Marin, J.M., Robert, C.P.: Population Monte Carlo. J. Comput. Graph. Stat. 13, 907–929 (2004)

    Article  MathSciNet  Google Scholar 

  • Cappe, O., Douc, R., Guillin, A., Marin, J., Robert, C.P.: Adaptive importance sampling in general mixture classes. Stat. Comput. 18 (2008). doi:10.1007/s11222-008-9059-x

  • Cornebise, J., Moulines, E., Olson, J.: Adaptive methods for sequential importance sampling with application to state space models. Stat. Comput. 18 (2008). doi:10.1007/s11222-008-9089-4

  • Doucet, A., Godsill, S.J., Andrieu, C.: On sequential Monte Carlo sampling methods for Bayesian filtering. Stat. Comput. 10, 197–208 (2000)

    Article  Google Scholar 

  • Fearnhead, P.: Computational methods for complex stochastic systems: A review of some alternatives to MCMC. Stat. Comput. 18, 151–171 (2008)

    Article  Google Scholar 

  • Gerlach, R., Chen, C.W.S.: Bayesian inference and model comparison for asymmetric smooth transition heteroskedastic models. Stat. Comput. 18 (2008). doi:10.1007/s11222-008-9063-1

  • Green, P.: Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika 82, 711–732 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  • Keith, J.M., Kroese, D.P., Sofronov, G.Y.: Adaptive independence samplers. Stat. Comput. 18 (2008). doi:10.1007/s11222-008-9070-2

  • Ren, Y., Ding, Y., Liang, F.: Adaptive evolutionary Monte Carlo algorithm for optimization with applications to sensor placement problems. Stat. Comput. 18 (2008). doi:10.1007/s11222-008-9079-6

  • Roberts, G.O., Rosenthal, J.S.: Optimal scaling for various metropolis-hastings algorithms. Stat. Sci. 16, 351–367 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  • Ter Braak, C.J.F., Vrugt, J.A.: Differential evolution Markov Chain with snooker updater and fewer chains. Stat. Comput. 18 (2008). doi:10.1007/s11222-008-9104-9

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  1. Dept of Mathematics and Statistics, Lancaster University, Lancaster, LA1 4YF, UK

    Paul Fearnhead

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  1. Paul Fearnhead
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Correspondence to Paul Fearnhead.

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Fearnhead, P. Editorial: Special issue on adaptive Monte Carlo methods. Stat Comput 18, 341–342 (2008). https://doi.org/10.1007/s11222-008-9107-6

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