Kernel density estimation for random fields (density estimation for random fields)

Michel Carbon, Lanh Tat Tran and Berlin Wu

Statistics & Probability Letters, 1997, vol. 36, issue 2, 115-125

Abstract: Kernel-type estimators of the multivariate density of stationary random fields indexed by multidimensional lattice points space are investigated. Sufficient conditions for kernel estimators to converge uniformly are obtained. The estimators can attain the optimal rates L[infinity] of convergence. The results apply to a large class of spatial processes.

Keywords: Random; field; Kernel; Bandwidth (search for similar items in EconPapers)
Date: 1997
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (32)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(97)00054-0
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:36:y:1997:i:2:p:115-125

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 ().