{"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/varepsilon-strong-simulation-of-the-convex","title":"$\\varepsilon$-strong simulation of the convex minorants of stable processes and meanders","arxiv_id":"1910.13273","date":"2019-10-29","proceeding":null,"authors":["Jorge Ignacio González Cázares","Aleksandar Mijatović","Gerónimo Uribe Bravo"],"abstract":"Using marked Dirichlet processes we characterise the law of the convex minorant of the meander for a certain class of L\\'evy processes, which includes subordinated stable and symmetric L\\'evy processes. We apply this characterisaiton to construct $\\varepsilon$-strong simulation ($\\varepsilon$SS) algorithms for the convex minorant of stable meanders, the finite dimensional distributions of stable meanders and the convex minorants of weakly stable processes. We prove that the running times of our $\\varepsilon$SS algorithms have finite exponential moments. We implement the algorithms in Julia 1.0 (available on GitHub) and present numerical examples supporting our convergence results.","url_abs":"http://arxiv.org/abs/1910.13273v1","url_pdf":"http://arxiv.org/pdf/1910.13273v1.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":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"varepsilon-strong-simulation-of-the-convex","repo_url":"https://github.com/jorgeignaciogc/StableMeander.jl","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}