Abrupt change in mean using block bootstrap and avoiding variance estimation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10383198" target="_blank" >RIV/00216208:11320/18:10383198 - isvavai.cz</a>
Alternative codes found
RIV/67985807:_____/18:00483674
Result on the web
<a href="https://doi.org/10.1007/s00180-017-0785-4" target="_blank" >https://doi.org/10.1007/s00180-017-0785-4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00180-017-0785-4" target="_blank" >10.1007/s00180-017-0785-4</a>

Result language
angličtina
Original language name
Abrupt change in mean using block bootstrap and avoiding variance estimation
Original language description
We deal with sequences of weakly dependent observations that are naturally ordered in time. Their constant mean 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 abrupt change in mean 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 the alternatives. A block bootstrap method is developed in order to obtain better approximations for the test's critical values. The validity of the bootstrap algorithm is shown. 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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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability

Project
<a href="/en/project/GJ15-04774Y" target="_blank" >GJ15-04774Y: Using copulas for modelling dependency structure of variables in the presence of covariates</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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