On two recent papers of Y. Kanazawa

M. C. Jones

Statistics & Probability Letters, 1995, vol. 24, issue 3, 269-271

Abstract: In two recent papers in this journal, Kanazawa (1993a, b) has described asymptotic equivalences between smoothing parameters minimising certain risk functions for histograms and kernel density estimators, respectively. In the current note, we (i) describe some well-known heuristic equivalences (known also to Kanazawa, but not mentioned in either paper) which explain why results are as they are, and (ii) put forward the more usual opposing views to Kanazawa's claim that his results "force us to entertain the possibility that the [Hellinger distance], not the conventional [integrated squared error], be the standard distance-based measure of discrepancy in density estimation".

Keywords: Akaike's; information; criterion; Hellinger; distance; Histogram; Kernel; density; estimator; Kullback-Liebler; loss; Weighted; integrated; squared; error (search for similar items in EconPapers)
Date: 1995
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0167-7152(94)00183-9
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:24:y:1995:i:3:p:269-271

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().