Variance estimation free tests for structural changes in regression
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F18%3A00483701" target="_blank" >RIV/67985807:_____/18:00483701 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-96941-1_24" target="_blank" >http://dx.doi.org/10.1007/978-3-319-96941-1_24</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-96941-1_24" target="_blank" >10.1007/978-3-319-96941-1_24</a>
Alternative languages
Result language
angličtina
Original language name
Variance estimation free tests for structural changes in regression
Original language description
A sequence of time-ordered observations possesses a trend, which 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. The change point methods presented here rely on ratio type test statistics based on maxima of the cumulative sums. These detection procedures for the change in regression are also robustified by considering a general score function. The main advantage of the proposed approach is that the variance of the observations neither has to be known nor estimated. The asymptotic distribution of the test statistic under the no change null hypothesis is derived. Moreover, we prove the consistency of the test under alternatives. The results are illustrated through a simulation study, which demonstrates computational efficiency of the procedures. A practical application to real data is presented as well.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Nonparametric Statistics : 3rd ISNPS, Avignon, France, June 2016
ISBN
978-3-319-96941-1
ISSN
2194-1009
e-ISSN
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Number of pages
17
Pages from-to
"February"
Publisher name
Springer
Place of publication
Cham
Event location
Avignon
Event date
Jun 11, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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