Počet záznamů: 1
On the Favorable Estimation for Fitting Heavy Tailed Data
- 1.
SYSNO ASEP 0342150 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název On the Favorable Estimation for Fitting Heavy Tailed Data Tvůrce(i) Stehlík, M. (AT)
Potocký, R. (SK)
Waldl, H. (AT)
Fabián, Zdeněk (UIVT-O) SAI, RIDZdroj.dok. Computational Statistics. - : Springer - ISSN 0943-4062
Roč. 25, č. 3 (2010), s. 485-503Poč.str. 19 s. Jazyk dok. eng - angličtina Země vyd. DE - Německo Klíč. slova heavy-tailed distribution ; exact likelihood ratio test ; T-score moment estimator ; insurance ; Basel II Vědní obor RIV BB - Aplikovaná statistika, operační výzkum CEZ AV0Z10300504 - UIVT-O (2005-2011) UT WOS 000280074100008 EID SCOPUS 77954535725 DOI 10.1007/s00180-010-0189-1 Anotace Assessment of heavy tailed data and its compound sums has many applications in insurance, auditing and operational risk capital assessment among others. In this paper, we compare the classical estimators (maximum likelihood, QQ and moment estimators) with the recently introduced robust estimators of “generalized median”, “trimmed mean” and estimators based on t-score moments. We derive the exact distribution of the likelihood ratio tests of homogeneity and simple hypothesis on the tail index of a two-parameter Pareto model. Such exact tests support the assessment of the performance of estimators. In particular, we discuss some problems that one can encounter when misemploying the log-normal assumption based methods supported by the Basel II framework. Real data and simulated examples illustrate the methods. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2011
Počet záznamů: 1