A nonparametric test of stationarity for independent data

Jeffrey D. Hart

Statistics & Probability Letters, 2016, vol. 108, issue C, 40-44

Abstract: A nonparametric test of stationarity for independent data is investigated. The test is based on comparing kernel density estimates calculated from subsamples of the data. Asymptotic distribution theory is developed and results of a modest simulation study are presented.

Keywords: Randomness statistics; Consistent test; Local alternatives (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715215301292
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:108:y:2016:i:c:p:40-44

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.2015.09.024

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 ().