Recursive asymmetric kernel density estimation for nonnegative data. Issue 2 (3rd April 2021)

• Record Type: Journal Article
• Authors: Kakizawa, Yoshihide
• Is Part Of: Journal of nonparametric statistics. Volume 33:Issue 2(2021)
• Page Start: 197
• Page End: 224
• Publication Date: 2021-04-03
• Subjects: Nonparametric density estimation -- boundary bias problem -- asymmetric kernel -- recursive estimator; primary 62G07 -- secondary 62G20; Nonparametric statistics -- Periodicals; 519.5
• DOI: 10.1080/10485252.2021.1928120
• Languages: English
• ISSNs: 1048-5252

Abstract

Abstract : Recursive nonparametric density estimation for nonnegative data is considered, using an asymmetric kernel with nonnegative support. It has a computational advantage in a situation where a huge number of data are sequentially collected. The recursive asymmetric kernel estimator keeps desirable asymptotic properties similar to the ordinary non-recursive asymmetric kernel estimator. Also, simulation studies and a real data analysis are performed for illustration.