An alternative distribution function estimation method using rational Bernstein polynomials

Autor:	Özlem Ege Oruç, Çetin Dişibüyük, Mahmut Sami Erdoğan
Rok vydání:	2019
Předmět:	TheoryofComputation_MISCELLANEOUS Computational Mathematics Monotone polygon Distribution function Applied Mathematics Nonparametric statistics Applied mathematics Estimator Basis function Function (mathematics) Bernstein polynomial Empirical distribution function Mathematics
Zdroj:	Journal of Computational and Applied Mathematics. 353:232-242
ISSN:	0377-0427
DOI:	10.1016/j.cam.2018.12.033
Popis:	This paper gives a general method for nonparametric distribution function estimation using the rational Bernstein polynomials as an alternative to the current estimators. The proposed new method is compared with Bernstein polynomials and empirical distribution function methods by simulation studies. The new method guarantees monotone nondecreasing function by applying linear constraints on the coefficients of the rational Bernstein basis functions and smooth the empirical distribution function. Furthermore, as a special case, it reduces to Bernstein polynomial estimator method. Some theoretical properties of the new estimator are investigated. Simulation study shows that the proposed estimator is preferable to the Bernstein polynomials and empirical distribution function estimator methods. (C) 2018 Elsevier B.V. All rights reserved.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c4577ec74f2460e51a467602be14c15 https://doi.org/10.1016/j.cam.2018.12.033 Zobrazit plný text záznamu Full Text from ScienceDirect