Change Detection in Autoregressive Time Series with Martingale Difference White Noise

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F11%3A10102930" target="_blank" >RIV/00216208:11320/11:10102930 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Change Detection in Autoregressive Time Series with Martingale Difference White Noise
Original language description
In this paper we study asymptotic properties of an efficient score statistic for testing changes in the parameter values of an autoregressive time series. We assume that the error process is a martingale difference sequence with known variance instead ofindependent identically distributed (i.i.d.) random variables. The procedure allows testing changes in the mean and in the autoregressive parameters separately. We present the invariance principle and the law of the iterated logarithm for martingale difference sequences and linear processes, and show that the asymptotic distribution of statistics under consideration is the same as in the case of i.i.d. errors.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
WDS'11 Proceedings of Contributed Papers: Part I - Mathematics and Computer Sciences
ISBN
978-80-7378-184-2
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
49-54
Publisher name
Matfyzpress
Place of publication
Prague
Event location
Praha
Event date
May 31, 2011
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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