Počet záznamů: 1  

Small Sample Robust Testing for Normality against Pareto Tails

  1. 1.
    SYSNO ASEP0376157
    Druh ASEPJ - Článek v odborném periodiku
    Zařazení RIVJ - Článek v odborném periodiku
    Poddruh JČlánek ve WOS
    NázevSmall Sample Robust Testing for Normality against Pareto Tails
    Tvůrce(i) Stehlík, M. (AT)
    Fabián, Zdeněk (UIVT-O) SAI, RID
    Střelec, L. (CZ)
    Zdroj.dok.Communications in Statistics: Simulation and Computation - ISSN 0361-0918
    Roč. 41, č. 7 (2012), s. 1167-1194
    Poč.str.28 s.
    Jazyk dok.eng - angličtina
    Země vyd.US - Spojené státy americké
    Klíč. slovaconsistency ; Hill estimator ; t-Hill estimator ; location functional ; Pareto tail ; power comparison ; returns ; robust tests for normality
    Vědní obor RIVBB - Aplikovaná statistika, operační výzkum
    CEZAV0Z10300504 - UIVT-O (2005-2011)
    UT WOS000304853800018
    EID SCOPUS84859857216
    DOI10.1080/03610918.2012.625849
    AnotaceThe aim of this article is to introduce the general form (so called RT class) of the robust and classical Jarque–Bera (JB) test based on the location functional. We introduce the two-step procedure which is optimal for testing against the individual or contaminated Pareto alternative. As a reference for such a contamination we consider different Pareto distributions. We also give practical guidelines for robust testing for normality against short- and heavy-tailed alternatives. We concentrate mainly on simulation results for moderate and small samples. However, we also prove consistency and asymptotic distribution for introduced tests. We show that as the suitable measure of nominal level of Pareto tail parameter we may take the t- Hill estimator introduced in the article. To guarantee the consistency of the whole procedure, we also prove the consistency of t-Hill estimator. The introduced general class of robust tests of the normality is illustrated at the selected datasets of financial time series.
    PracovištěÚstav informatiky
    KontaktTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Rok sběru2013