Bootstrapping Not Independent and Not Identically Distributed Data

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F22%3A00567128" target="_blank" >RIV/67985807:_____/22:00567128 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11320/22:10453827
Result on the web
<a href="https://dx.doi.org/10.3390/math10244671" target="_blank" >https://dx.doi.org/10.3390/math10244671</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/math10244671" target="_blank" >10.3390/math10244671</a>

Result language
angličtina
Original language name
Bootstrapping Not Independent and Not Identically Distributed Data
Original language description
Classical normal asymptotics could bring serious pitfalls in statistical inference, because some parameters appearing in the limit distributions are unknown and, moreover, complicated to estimated (from a theoretical as well as computational point of view). Due to this, plenty of stochastic approaches for constructing confidence intervals and testing hypotheses cannot be directly applied. Bootstrap seems to be a plausible alternative. A methodological framework for bootstrapping not independent and not identically distributed data is presented together with theoretical justification of the proposed procedures. Among others, bootstrap laws of large numbers and central limit theorems are provided. The developed methods are utilized in insurance and psychometry.
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
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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