Approximations for \(F\) -tests which are ratios of sums of squares of independent variables with a model close to the normal

DOI10.1007/s11749-006-0036-4zbMath1196.62018OpenAlexW1997877428MaRDI QIDQ1019111

Alfonso García-Pérez

Publication date: 27 May 2009

Published in: Test (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11749-006-0036-4

zbMATH Keywords

saddlepoint approximationvon Mises expansiontail area influence functionrobustness in hypotheses testingrobustness of validity plot

Mathematics Subject Classification ID

Parametric hypothesis testing (62F03) Robustness and adaptive procedures (parametric inference) (62F35) Approximations to statistical distributions (nonasymptotic) (62E17) Graphical methods in statistics (62A09)

Related Items (4)

A von Mises approximation to the small sample distribution of the trimmed mean ⋮ Another look at the tail area influence function ⋮ A linear approximation to the power function of a test ⋮ An Approximation to the Small Sample Distribution of the Trimmed Mean for Gaussian Mixture Models

Cites Work

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• Bounds on AREs for restricted classes of distributions defined via tail- orderings
• Von Mises approximation of the critical value of a test
• Chi-square tests under models close to the normal distribution
• Bartlett's, Cochran's, and Hartley's Tests on Variances are Liberal When the Underlying Distribution is Long-Tailed
• Is the t Test Really Conservative When the Parent Distribution is Long-Tailed?
• Saddlepoint approximations for estimating equations
• A tail area influence function and its application to testing
• Saddle point approximation for the distribution of the sum of independent random variables
• The Influence Curve and Its Role in Robust Estimation
• Relation between the shape of population distribution and the robustness of four simple test statistics
• On Robustness for Hypotheses Testing
• t-Tests with Models Close to the Normal Distribution
• Mises’ Theorem on the Asymptotic Behavior of Functionals of Empirical Distribution Functions and Its Statistical Applications
• NON-NORMALITY AND TESTS ON VARIANCES

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