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
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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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
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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