On the Rate of Approximations for Maximum Likelihood Tests in Change-Point Models
Edit Gombay and
Journal of Multivariate Analysis, 1996, vol. 56, issue 1, 120-152
We study the asymptotics of maximum-likelihood ratio-type statistics for testing a sequence of observations for no change in parameters against a possible change while some nuisance parameters remain constant over time. We obtain extreme value as well as Gaussian-type approximations for the likelihood ratio. We get necessary and sufficient conditions for the weak convergence of supremum andLp-functionals of the likelihood ration process. We also approximate the maximum likelihood ratio with Ornstein-Uhlenbeck processes and obtain bounds for the rate of approximation. We show that the Ornstein-Uhlenbeck approach is superior to the extreme value limit in case of moderate sample sizes.
Keywords: likelihood; ratio; processes; maximum; likelihood; estimators; weighted; approximations; extreme; value; Brownian; bridge; (null) (search for similar items in EconPapers)
References: Add references at CitEc
Citations: View citations in EconPapers (10) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:56:y:1996:i:1:p:120-152
Ordering information: This journal article can be ordered from
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 Dana Niculescu ().