Počet záznamů: 1
Bootstrapping Not Independent and Not Identically Distributed Data
- 1.
SYSNO ASEP 0567128 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Bootstrapping Not Independent and Not Identically Distributed Data Tvůrce(i) Hrba, M. (CZ)
Maciak, M. (CZ)
Peštová, Barbora (UIVT-O) RID, SAI
Pešta, M. (CZ)Číslo článku 4671 Zdroj.dok. Mathematics. - : MDPI
Roč. 10, č. 24 (2022)Poč.str. 26 s. Jazyk dok. eng - angličtina Země vyd. CH - Švýcarsko Klíč. slova bootstrap ; statistical inference ; asymptotic normality ; weakly dependent data ; not identically distributed data ; moving block bootstrap ; law of large numbers ; central limit theorem ; psychometric evaluation ; non-life insurance Obor OECD Statistics and probability CEP GA21-03658S GA ČR - Grantová agentura ČR Způsob publikování Open access Institucionální podpora UIVT-O - RVO:67985807 UT WOS 000902904500001 EID SCOPUS 85144741403 DOI 10.3390/math10244671 Anotace 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. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2023 Elektronická adresa https://dx.doi.org/10.3390/math10244671
Počet záznamů: 1