Recursive nonparametric predictive for a discrete regression model

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• dc.contributor.author Cappello, Lorenzo
• dc.contributor.author Walker, Stephen G.
• dc.date.accessioned 2025-10-24T15:59:16Z
• dc.date.available 2025-10-24T15:59:16Z
• dc.date.issued 2026
• dc.date.updated 2025-10-24T15:59:16Z
• dc.description Data de publicació electrònica: 16-09-2025
• dc.description.abstract A recursive algorithm is proposed to estimate a set of distribution functions indexed by a regressor variable. The procedure is fully nonparametric and has a Bayesian motivation and interpretation. Indeed, the recursive algorithm follows a certain Bayesian update, defined by the predictive distribution of a Dirichlet process mixture of linear regression models. Consistency of the algorithm is demonstrated under mild assumptions, and numerical accuracy in finite samples is shown via simulations and real data examples. The algorithm is very fast to implement, it is parallelizable, sequential, and requires limited computing power.
• dc.description.sponsorship Ministry of Economy and Competitiveness grant PID2022-138268NB-I00, financed by MCIN / AEI /10.13039/50-1100011033, FSE + MTM2015-67304-P and FEDER, EU; and the Spanish Ministry of Economy and Competitiveness grant Ramon y Cajal 2022 RYC20-22038467-I, financed by MCIN/AEI/10.13039/501100011033 and FSE+. The second author is partially funded by NSF grants DMS 1,506,879 and 1612891.
• dc.format.mimetype application/pdf
• dc.identifier.citation Cappello L, Walker SG. Recursive nonparametric predictive for a discrete regression model. Computational Statistics and Data Analysis. 2026;215:108275. DOI: 10.1016/j.csda.2025.108275
• dc.identifier.doi http://dx.doi.org/10.1016/j.csda.2025.108275
• dc.identifier.issn 0167-9473
• dc.identifier.uri http://hdl.handle.net/10230/71653
• dc.language.iso eng
• dc.publisher Elsevier
• dc.relation.ispartof Computational Statistics and Data Analysis. 2026;215:108275
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PE/PID2022-138268NB-I00
• dc.rights © 2025 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/
• dc.subject.keyword Nonparametric density estimation
• dc.subject.keyword Distribution regression
• dc.subject.keyword Recursive algorithm
• dc.subject.keyword Bayesian nonparametrics
• dc.title Recursive nonparametric predictive for a discrete regression model
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion