Multivariate generalized Birnbaum—Saunders kernel density estimators. Issue 18 (17th September 2018)

• Record Type: Journal Article
• Authors: Zougab, N.; Harfouche, L.; Ziane, Y.; Adjabi, S.
• Is Part Of: Communications in statistics. Volume 47:Issue 18(2018)
• Page Start: 4534
• Page End: 4555
• Publication Date: 2018-09-17
• Subjects: Integrated squared error -- Multiplicative bias correction -- Multivariate non negative data; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2017.1377252
• Languages: English
• ISSNs: 0361-0926

Abstract

ABSTRACT: In this article, we first propose the classical multivariate generalized Birnbaum–Saunders kernel estimator for probability density function estimation in the context of multivariate non negative data. Then, we apply two multiplicative bias correction (MBC) techniques for multivariate kernel density estimator. Some properties (bias, variance, and mean integrated squared error) of the corresponding estimators are also investigated. Finally, the performances of the classical and MBC estimators based on family of generalized Birnbaum–Saunders kernels are illustrated by a simulation study.