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On the Bayesian Interpretation of Penalized Statistical Estimators
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SYSNO ASEP 0579680 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title On the Bayesian Interpretation of Penalized Statistical Estimators Author(s) Kalina, Jan (UIVT-O) RID, SAI, ORCID
Peštová, Barbora (UIVT-O) RID, SAISource Title Artificial Intelligence and Soft Computing. 22nd International Conference, ICAISC 2023, Proceedings, Part 2. - Cham : Springer, 2023 / Rutkowski L. ; Scherer R. ; Korytkowski M. ; Pedrycz W. ; Tadeusiewicz R. ; Zurada J. M. - ISBN 978-3-031-42507-3 Pages s. 343-352 Number of pages 10 s. Publication form Print - P Action ICAISC 2023: International Conference on Artificial Intelligence and Soft Computing /22./ Event date 18.07.2023 - 22.07.2023 VEvent location Zakopane Country PL - Poland Event type WRD Language eng - English Country CH - Switzerland Keywords Bayesian estimation ; regularization ; penalization ; robustness ; regression Subject RIV BA - General Mathematics OECD category Statistics and probability R&D Projects GA21-05325S GA ČR - Czech Science Foundation (CSF) Institutional support UIVT-O - RVO:67985807 UT WOS 001155257400031 EID SCOPUS 85174447437 DOI 10.1007/978-3-031-42508-0_31 Annotation The aim of this work is to search for intuitive interpretations of penalized statistical estimators. Penalized estimates of the parameters of three models obtained by Bayesian reasoning are explained here to correspond to the intuition. First, the paper considers Bayesian estimates of the mean and covariance matrix for the multivariate normal distribution. Second, a connection of a robust regularized version of Mahalanobis distance with Bayesian estimation is discussed. Third, regularization networks, which represent a common nonparametric tool for regression modeling, are presented as Bayesian methods as well. On the whole, selected important multivariate and/or regression models are considered and novel interpretations are formulated. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2024 Electronic address https://doi.org/10.1007/978-3-031-42508-0_31
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