{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/getting-started-with-particle-metropolis","title":"Getting Started with Particle Metropolis-Hastings for Inference in Nonlinear Dynamical Models","arxiv_id":"1511.01707","date":"2015-11-05","proceeding":null,"authors":["Johan Dahlin","Thomas B. Schön"],"abstract":"This tutorial provides a gentle introduction to the particle\nMetropolis-Hastings (PMH) algorithm for parameter inference in nonlinear\nstate-space models together with a software implementation in the statistical\nprogramming language R. We employ a step-by-step approach to develop an\nimplementation of the PMH algorithm (and the particle filter within) together\nwith the reader. This final implementation is also available as the package\npmhtutorial in the CRAN repository. Throughout the tutorial, we provide some\nintuition as to how the algorithm operates and discuss some solutions to\nproblems that might occur in practice. To illustrate the use of PMH, we\nconsider parameter inference in a linear Gaussian state-space model with\nsynthetic data and a nonlinear stochastic volatility model with real-world\ndata.","url_abs":"http://arxiv.org/abs/1511.01707v8","url_pdf":"http://arxiv.org/pdf/1511.01707v8.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"getting-started-with-particle-metropolis","repo_url":"https://github.com/compops/pmh-tutorial","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"state-space-models","task_name":"State Space Models"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}