Change Point Detection in Autoregression Without Variability Estimation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F17%3A00484133" target="_blank" >RIV/67985807:_____/17:00484133 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11320/17:10366005
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Change Point Detection in Autoregression Without Variability Estimation
Original language description
A sequence of time-ordered observations follows an autoregressive model of order one and its parameter is possibly subject to change at most once at some unknown time point. The aim is to test whether such an unknown change has occurred or not. A change point method presented here rely on a ratio type test statistic based on the maxima of cumulative sums. The main advantage of the proposed approach is that the variance of the observations neither has to be known nor estimated. Asymptotic distribution of the test statistic under the no change null hypothesis is derived. Moreover, we prove the consistency of the test under the alternative. The results are illustrated through a simulation study, which demonstrates computational e
Czech name
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Czech description
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Project
<a href="/en/project/GBP402%2F12%2FG097" target="_blank" >GBP402/12/G097: DYME-Dynamic Models in Economics</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the International work-conference on Time Series 2017
ISBN
978-84-17293-01-7
ISSN
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e-ISSN
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Number of pages
12
Pages from-to
674-685
Publisher name
Godel Editorial
Place of publication
Granada
Event location
Granada
Event date
Sep 18, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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