On the utility of asymptotic bandwidth selectors for spatially adaptive kernel density estimation

Tilman M. Davies, Claire R. Flynn and Martin L. Hazelton

Statistics & Probability Letters, 2018, vol. 138, issue C, 75-81

Abstract: Implementation of the spatially adaptive kernel estimator relies on choice of a ‘global bandwidth’. We derive the closed-form asymptotic bias for this estimator with the aim of developing relevant selectors, and note non-uniform convergence hinders its usability for this purpose.

Keywords: Global bandwidth; AMISE; Spatial point process; Kernel smoothing; Normal scale rule (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715218301123
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:138:y:2018:i:c:p:75-81

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

DOI: 10.1016/j.spl.2018.02.067

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 ().