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https://hdl.handle.net/10316/92032
Title: | Bandwidth selection for kernel density estimation: a Hermite series-based direct plug-in approach | Authors: | Tenreiro, Carlos | Issue Date: | 2020 | Publisher: | Taylor and Francis | Serial title, monograph or event: | Journal of Statistical Computation and Simulation | Volume: | 90 | Issue: | 18 | Abstract: | In this paper we propose a new class of Hermite series-based direct plug-in bandwidth selectors for kernel density estimation and we describe their asymptotic and finite sample behaviours. Unlike the direct plug-in bandwidth selectors considered in the literature, the proposed methodology does not involve multistage strategies and reference distributions are no longer needed. The new bandwidth selectors show a good finite sample performance when the underlying probability density function presents not only "easy-to-estimate" but also "hard-to-estimate" distribution features. This quality, that is not shared by other widely used bandwidth selectors as the classical plug-in or the least-square cross-validation methods, is the most significant aspect of the Hermite series-based direct plug-in approach to bandwidth selection. | URI: | https://hdl.handle.net/10316/92032 | ISSN: | 0094-9655 1563-5163 |
DOI: | 10.1080/00949655.2020.1804571 | Rights: | embargoedAccess |
Appears in Collections: | I&D CMUC - Artigos em Revistas Internacionais |
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