Dependent versions of a central limit theorem for the squared length of a sample mean

Pentti Saikkonen

Statistics & Probability Letters, 1995, vol. 22, issue 3, 185-194

Abstract: Portnoy (1988) has proved a central limit theorem for the squared length of a sample mean by assuming that the underlying random vectors are independent and identically distributed and that their dimension increases with the sample size. Extensions of this result to martingale differences, useful in time series hypothesis testing, are derived and applied to a test of serial correlation.

Keywords: Central; limit; theorem; Increasing; dimension; Martingale; difference (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)00066-H
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:22:y:1995:i:3:p:185-194

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 ().