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Title: Confidence intervals for large non- centrality parameter
Authors: Inácio, S.
Oliveira, M.
Mexia, J.T.
Editors: Zmyślony, R.
Keywords: asymptotic linearity
non-centrality parameters
highly significant F tests
measure relevance
Issue Date: 2-May-2015
Publisher: Discussiones Mathematicae Probability and Statistics
Citation: Inácio, S. T., Oliveira, M. M., Mexia, J.T. 2015. Confidence intervals for large non-centrality parameter. Discussiones Mathematicae Probability and Statistics 35.45–56 doi:10.7151/dmps.1175. ISSN 1509-9423,ISSN 2084-0381.
Abstract: We use asymptotic linearity to derive confidence intervals for large noncentrality parameters. These results enable us to measure relevance of effects and interactions in multifactors models when we get highly statistically significant the values of F tests statistics. We show how to use our approach by considering two sets of data as application examples.
ISSN: 2084-0381
Type: article
Appears in Collections:CIMA - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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