Estimation of Error Variance in One-Way Random Model.
Estimation of parameters of mean and variance in two-stage linear models
The paper deals with the estimation of unknown vector parameter of mean and scalar parameters of variance as well in two-stage linear model, which is a special type of mixed linear model. The necessary and sufficient condition for the existence of uniformly best unbiased estimator of parameter of means is given. The explicite formulas for these estimators and for the estimators of the parameters of variance as well are derived.
Estimation of polynomials in the regression model
Let be an -dimensional random vector which is distributed. A minimum variance unbiased estimator is given for provided is an unbiasedly estimable functional of an unknown -dimensional parameter .
Estimation of simple linear regression model using ranked set sampling.
Estimation of the first order parameters in the twoepoch linear model
The linear regression model, where the mean value parameters are divided into stable and nonstable part in each of both epochs of measurement, is considered in this paper. Then, equivalent formulas of the best linear unbiased estimators of this parameters in both epochs using partitioned matrix inverse are derived.
Estimation of the hazard function in a semiparametric model with covariate measurement error
We consider a failure hazard function, conditional on a time-independent covariate Z, given by . The baseline hazard function and the relative risk both belong to parametric families with . The covariate Z has an unknown density and is measured with an error through an additive error model U = Z + ε where ε is a random variable, independent from Z, with known density . We observe a n-sample (Xi, Di, Ui), i = 1, ..., n, where Xi is the minimum between the failure time and the censoring time, and...
Estimation of the output deviation norm for uncertain, discrete-time nonlinear systems in a state dependent form
Numerical evaluation of the optimal nonlinear robust control requires estimating the impact of parameter uncertainties on the system output. The main goal of the paper is to propose a method for estimating the norm of an output trajectory deviation from the nominal trajectory for nonlinear uncertain, discrete-time systems. The measure of the deviation allows us to evaluate the robustness of any designed controller. The first part of the paper concerns uncertainty modelling for nonlinear systems...
Estimation of the preference relation on the basis of multiple pairwise comparisons
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
Estimation récursive des paramètres d'un modèle de régression, variant au cours du temps
Estimation Under Linear Regression Models.
Estimations of covariance components in mixed linear models
An estimation of the linear function of elements of unknown matrices in the covariance components model is presented.
Estimator selection in the gaussian setting
We consider the problem of estimating the mean of a Gaussian vector with independent components of common unknown variance . Our estimation procedure is based on estimator selection. More precisely, we start with an arbitrary and possibly infinite collection of estimators of based on and, with the same data , aim at selecting an estimator among with the smallest Euclidean risk. No assumptions on the estimators are made and their dependencies with respect to may be unknown. We establish...
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.
Estimators for epidemic alternatives
We introduce and study the behavior of estimators of changes in the mean value of a sequence of independent random variables in the case of so called epidemic alternatives which is one of the variants of the change point problem. The consistency and the limit distribution of the estimators developed for this situation are shown. Moreover, the classical estimators used for `at most change' are examined for the studied situation.
Étude des propriétés asymptotiques des estimateurs des moindres carrés pour des problèmes de régression à phases multiples
Étude d'un modèle factoriel d'analyse de la variance comme modèle linéaire généralisé
Étude géométrique de l'analyse de la variance multidimensionnelle