title: Varying kernel density estimation on ℝ.
abstract: In this article a new nonparametric density estimator based on the sequence of asymmetric kernels is proposed. This method is natural when estimating an unknown density function of a positive random variable. The rates of Mean Squared Error, Mean Integrated Squared Error, and theL1-consistency are investigated. Simulation studies are conducted to compare a new estimator and its modified version with traditional kernel density construction.
authors.affiliation: West Virginia University, USA; National Institute for Occupational Safety and Health, USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Mnatsakanov
authors.affiliation: West Virginia University, USA; National Institute for Occupational Safety and Health, USA.
authors.forename: Khachatur
authors.initials: K
authors.lastname: Sarkisian
keywords: L1-consistency; Mean Integrated Squared Error; Mean Squared Error; Varying kernel density estimator; δ-sequence