Confidence intervals for large non-centrality parameters

• Autorzy: Sonia Inacio , Manuela M. Oliveira , João Tiago Mexia
• Języki publikacji: EN

Abstrakty

EN

We use asymptotic linearity to derive confidence intervals for large non-centrality 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.

Słowa kluczowe

EN

asymptotic linearity; non-centrality parameters; highly significant; F tests; measure relevance

Kategorie tematyczne

• 62F03: Hypothesis testing

• Wydawca: Faculty of Mathematics, Computer Science and Econometrics, University of Zielona Góra
• Czasopismo: Discussiones Mathematicae Probability and Statistics
• Rocznik: 2015
• Tom: 35
• Numer: 1-2
• Strony: 45-56

Daty

wydano

2015

otrzymano

2015-03-15

Twórcy

autor

Sonia Inacio

• FCT New University of Lisbon, Department of Mathematics, Portugal

autor

Manuela M. Oliveira

• University of Évora, Department of Mathematics, Center for Research on Mathematics and its Applications, Portugal

autor

João Tiago Mexia

• FCT New University of Lisbon, Department of Mathematics, Portugal

Bibliografia

• [1] D. Ferreira, S.S. Ferreira, C. Nunes and S. Inácio, Inducing pivot variables and non-centrality parameters in elliptical distributions, AIP Conf. Proc. 1558 (2013), 833.
• [2] J.T. Mexia, Assymptotic Chi-squared Tests, Design and Log-Linear Models (Trabalhos de Investigaçăo, 1. Departamento de Matemática, Faculdade de Cięncias e Tecnologia, Universidade Nova de Lisboa, 1992).
• [3] J.T. Mexia and M.M. Oliveira, Asymptotic linearity and limit distributions, approximations, Journal of Statistical Planning and Inference 140 (2011), 353-357.
• [4] M.M. Oliveira and J.T. Mexia, ANOVA like analysis of matched series of studies with a common structure, Journal of Statistical Planning and Inference 137 (2007), 1862-1870.
• [5] C. Nunes, S.S. Ferreira and J.T. Mexia, Fixed effects NOVA: an extension to samples with random size, Journal of Statistical Computation and Simulation 84 (2014), 2316-2328.
• [6] H. Scheffé, The Analysis of Variance (New York-John Wiley & Sons, 1959).

Identyfikatory

DOI

10.7151/dmps.1175