Varying kernel density estimation on R+

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 the L1-consistency are investigated. Simulation studies are conducted to compare a new estimator and its modified version with traditional kernel density construction.

MoreLess

Year of publication:	2012
Authors:	Mnatsakanov, Robert ; Sarkisian, Khachatur
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 82.2012, 7, p. 1337-1345
Publisher:	Elsevier
Subject:	Varying kernel density estimator \| Mean Squared Error \| Mean Integrated Squared Error \| δ-sequence \| L1-consistency

Online Resource

Check full text access |

More access options

Check Google Scholar

In libraries world-wide (WorldCat)

In German libraries (KVK)

subito order

I need help

More details

Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011039877