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Selective F tests for sub-normal models

Célia Maria Pinto Nunes;  João Tiago Mexia — 2003

Discussiones Mathematicae Probability and Statistics

F tests that are specially powerful for selected alternatives are built for sub-normal models. In these models the observation vector is the sum of a vector that stands for what is measured with a normal error vector, both vectors being independent. The results now presented generalize the treatment given by Dias (1994) for normal fixed-effects models, and consider the testing of hypothesis on the ordering of mean values and components.

Generalized F tests in models with random perturbations: the gamma case

Célia Maria Pinto Nunes;  Sandra Maria Bargão Saraiva Ferreira;  Dário Jorge da Conceição Ferreira — 2009

Discussiones Mathematicae Probability and Statistics

Generalized F tests were introduced for linear models by Michalski and Zmyślony (1996, 1999). When the observations are taken in not perfectly standardized conditions the F tests have generalized F distributions with random non-centrality parameters, see Nunes and Mexia (2006). We now study the case of nearly normal perturbations leading to Gamma distributed non-centrality parameters.

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