Limiting values of large deviation probabilities of quadratic statistics

G. A. M. Jeurnink and W. C. M. Kallenberg

Journal of Multivariate Analysis, 1990, vol. 35, issue 2, 168-185

Abstract: Application of exact Bahadur efficiencies in testing theory or exact inaccuracy rates in estimation theory needs evaluation of large deviation probabilities. Because of the complexity of the expressions, frequently a local limit of the nonlocal measure is considered. Local limits of large deviation probabilities of general quadratic statistics are obtained by relating them to large deviation probabilities of sums of k-dimensional random vectors. The results are applied, e.g., to generalized Cramér-von Mises statistics, including the Anderson-Darling statistic, Neyman's smooth tests, and likelihood ratio tests.

Keywords: exact; Bahadur; efficiency; large; deviations; generalized; Cramer-von; Mises; statistics; quadratic; statistics; Hilbert-Schmidt; operator; eigenvalues; eigenfunctions; Neyman's; smooth; tests; likelihood; ratio; tests (search for similar items in EconPapers)
Date: 1990
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0047-259X(90)90023-B
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:jmvana:v:35:y:1990:i:2:p:168-185

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

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().