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V-Subgeometric ergodicity for a Hastings-Metropolis algorithm

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  • Fort, Gersende
  • Moulines, Eric

Abstract

We study the symmetric random-walk Hastings-Metropolis algorithm in situations where the density is not log-concave in the tails. We show that, under mild technical conditions this algorithm is V-ergodic at a subgeometrical rate.

Suggested Citation

  • Fort, Gersende & Moulines, Eric, 2000. "V-Subgeometric ergodicity for a Hastings-Metropolis algorithm," Statistics & Probability Letters, Elsevier, vol. 49(4), pages 401-410, October.
    • Handle: RePEc:eee:stapro:v:49:y:2000:i:4:p:401-410
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    References listed on IDEAS

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    1. Jarner, Søren Fiig & Hansen, Ernst, 2000. "Geometric ergodicity of Metropolis algorithms," Stochastic Processes and their Applications, Elsevier, vol. 85(2), pages 341-361, February.
    2. O. Stramer & R. L. Tweedie, 1999. "Langevin-Type Models I: Diffusions with Given Stationary Distributions and their Discretizations," Methodology and Computing in Applied Probability, Springer, vol. 1(3), pages 283-306, October.
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    Cited by:

    1. Sanha Noh, 2020. "Posterior Inference on Parameters in a Nonlinear DSGE Model via Gaussian-Based Filters," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 795-841, December.
    2. Fort, G. & Moulines, E., 2003. "Polynomial ergodicity of Markov transition kernels," Stochastic Processes and their Applications, Elsevier, vol. 103(1), pages 57-99, January.
    3. Mika Meitz & Pentti Saikkonen, 2022. "Subgeometrically ergodic autoregressions with autoregressive conditional heteroskedasticity," Papers 2205.11953, arXiv.org, revised Apr 2023.
    4. Sarantsev, Andrey, 2021. "Sub-exponential rate of convergence to equilibrium for processes on the half-line," Statistics & Probability Letters, Elsevier, vol. 175(C).
    5. Mika Meitz & Pentti Saikkonen, 2019. "Subgeometric ergodicity and $\beta$-mixing," Papers 1904.07103, arXiv.org, revised Apr 2019.
    6. Douc, Randal & Fort, Gersende & Guillin, Arnaud, 2009. "Subgeometric rates of convergence of f-ergodic strong Markov processes," Stochastic Processes and their Applications, Elsevier, vol. 119(3), pages 897-923, March.

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