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Geometric aspects of robust testing for normality and sphericity

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F17%3A43910817" target="_blank" >RIV/62156489:43110/17:43910817 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1080/07362994.2016.1273785" target="_blank" >http://dx.doi.org/10.1080/07362994.2016.1273785</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1080/07362994.2016.1273785" target="_blank" >10.1080/07362994.2016.1273785</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Geometric aspects of robust testing for normality and sphericity

  • Original language description

    Stochastic robustness of control systems under random excitation motivates challenging developments in geometric approach to robustness. The assumption of normality is rarely met when analyzing real data and thus the use of classic parametric methods with violated assumptions can result in the inaccurate computation of p-values, effect sizes, and confidence intervals. Therefore, quite naturally, research on robust testing for normality has become a new trend. Robust testing for normality can have counterintuitive behavior, some of the problems have been introduced in Stehlík et al. [Chemometrics and Intelligent Laboratory Systems 130 (2014): 98-108]. Here we concentrate on explanation of small-sample effects of normality testing and its robust properties, and embedding these questions into the more general question of testing for sphericity. We give geometric explanations for the critical tests. It turns out that the tests are robust against changes of the density generating function within the class of all continuous spherical sample distributions.

  • Czech name

  • Czech description

Classification

  • 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

Result continuities

  • Project

    <a href="/en/project/GA16-07089S" target="_blank" >GA16-07089S: Robust approach to testing for normality of error terms in econometric models</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2017

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Stochastic Analysis and Applications

  • ISSN

    0736-2994

  • e-ISSN

  • Volume of the periodical

    35

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    22

  • Pages from-to

    511-532

  • UT code for WoS article

    000394450600008

  • EID of the result in the Scopus database

    2-s2.0-85011710518