A3 Book section, Chapters in research books
Ergonomic and Reliable Bayesian Inference with Adaptive Markov Chain Monte Carlo (2020)
Vihola, M. (2020). Ergonomic and Reliable Bayesian Inference with Adaptive Markov Chain Monte Carlo. In N. Balakrishnan, T. Colton, B. Everitt, W. Piegorsch, F. Ruggeri, & J. L. Teugels (Eds.), Wiley StatsRef : Statistics Reference Online (pp. 1-12). John Wiley & Sons. https://doi.org/10.1002/9781118445112.stat08286
JYU authors or editors
Publication details
All authors or editors: Vihola, Matti
Parent publication: Wiley StatsRef : Statistics Reference Online
Parent publication editors: Balakrishnan, N.; Colton, T.; Everitt, B.; Piegorsch, W.; Ruggeri, F.; Teugels, J. L.
eISBN: 978-1-118-44511-2
Publication year: 2020
Pages range: 1-12
Publisher: John Wiley & Sons
Publication country: United States
Publication language: English
DOI: https://doi.org/10.1002/9781118445112.stat08286
Publication open access: Not open
Publication channel open access:
Abstract
Adaptive Markov chain Monte Carlo (MCMC) methods provide an ergonomic way to perform Bayesian inference, imposing mild modeling constraints and requiring little user specification. The aim of this section is to provide a practical introduction to selected set of adaptive MCMC methods and to suggest guidelines for choosing appropriate methods for certain classes of models. We consider simple unimodal targets with random-walk-based methods, multimodal target distributions with parallel tempering, and Bayesian hidden Markov models using particle MCMC. The section is complemented by an easy-to-use open-source implementation of the presented methods in Julia, with examples.
Keywords: Markov chains; Monte Carlo methods; Bayesian analysis; methods
Contributing organizations
Related projects
- Exact approximate Monte Carlo methods for complex Bayesian inference
- Vihola, Matti
- Research Council of Finland
- Exact approximate Monte Carlo methods for complex Bayesian inference (research costs)
- Vihola, Matti
- Research Council of Finland
- Scalable methods for reliable Bayesian inference (SCALEBAYES)
- Vihola, Matti
- Research Council of Finland
Ministry reporting: Yes
Reporting Year: 2020
JUFO rating: 2