Deux structures statistiques fondamentales en analyse de la variance univariée et multivariée
Ein Beitrag zur Analyse von Zeitreihen: Die Quotientenmethode, eine Variante der "Variate Difference" Methode
Ergänzung zu Â?Ein Beitrag zur Analyse von Zeitreihen: Die Quotientenmethode, eine Variante der 'Variate Difference' Methode", Metrika, Vol. 16, 1970, Fasc. 2 - 3
Error analysis of a pairwise summation algorithm to compute the sample variance.
Estimation de certaines interactions en analyse de variance
Estimation of covariance components in a repeated regression experiment
Estimation of Error Variance in One-Way Random Model.
Estimation of the variance components in the linear regression model
Estimation of variance components in mixed linear models
The MINQUE of the linear function of the unknown variance-components parameter in mixed linear model under linear restrictions of the type is defined and derived. As an illustration of this estimator the example of the one-way classification model with the restrictions , where , is given.
Estimation of variance components in random models
Estimators and tests for variance components in cross nested orthogonal designs
Explicit expressions of UMVUE for variance components are obtained for a class of models that include balanced cross nested random models. These estimators are used to derive tests for the nullity of variance components. Besides the usual F tests, generalized F tests will be introduced. The separation between both types of tests will be based on a general theorem that holds even for mixed models. It is shown how to estimate the p-value of generalized F tests.
Étude d'un modèle factoriel d'analyse de la variance comme modèle linéaire généralisé
Étude géométrique de l'analyse de la variance multidimensionnelle
Exact distribution for the generalized F tests
Generalized F statistics are the quotients of convex combinations of central chi-squares divided by their degrees of freedom. Exact expressions are obtained for the distribution of these statistics when the degrees of freedom either in the numerator or in the denominator are even. An example is given to show how these expressions may be used to check the accuracy of Monte-Carlo methods in tabling these distributions. Moreover, when carrying out adaptative tests, these expressions enable us to estimate...
Explicit forms of block matrices in unbalanced cross classification
Extensions de l'analyse de la variance : l'analyse bayésienne des comparaisons
F and selective F tests with balanced cross-nesting and associated models
F tests and selective F tests for fixed effects part of balanced models with cross-nesting are derived. The effects of perturbations in the numerator and denominator of the F statistics are considered.
F-tests for generalized linear hypotheses in subnormal models
When the measurement errors may be assumed to be normal and independent from what is measured a subnormal model may be used. We define a linear and generalized linear hypotheses for these models, and derive F-tests for them. These tests are shown to be UMP for linear hypotheses as well as strictly unbiased and strongly consistent for these hypotheses. It is also shown that the F-tests are invariant for regular transformations, possess structural stability and are almost strongly consistent for generalized...
Graphics card as a cheap supercomputer
The current powerful graphics cards, providing stunning real-time visual effects for computer-based entertainment, have to accommodate powerful hardware components that are able to deliver the photo-realistic simulation to the end-user. Given the vast computing power of the graphics hardware, its producers very often offer a programming interface that makes it possible to use the computational resources of the graphics processors (GPU) to more general purposes. This step gave birth to the so-called...
How the design of an experiment influences the nonsensitiveness regions in models with variance components
Nonsensitiveness regions for estimators of linear functions, for confidence ellipsoids, for the level of a test of a linear hypothesis on parameters and for the value of the power function are investigated in a linear model with variance components. The influence of the design of an experiment on the nonsensitiveness regions mentioned is numerically demonstrated and discussed on an example.