Estimation and experimental design in a linear regression model using prior information
Estimation and prediction in regression models with random explanatory variables [Book]
Estimation and testing of cointegration relationships with strongly seasonal monthly data
Estimation and tests in finite mixture models of nonparametric densities
The aim is to study the asymptotic behavior of estimators and tests for the components of identifiable finite mixture models of nonparametric densities with a known number of components. Conditions for identifiability of the mixture components and convergence of identifiable parameters are given. The consistency and weak convergence of the identifiable parameters and test statistics are presented for several models.
Estimation and tests of the discrete probability law based on the empirical generating function, (two dimensional case).
Estimation asymptotique dans certains modèles de Geffroy linéaires
Estimation automatique de la densité
Estimation by Minimum-Discrepancy Methods
Estimation de certaines interactions en analyse de variance
Estimation de la densité du recuit simulé
Estimation de la densité par projection sur un sous-espace de dimension finie
Estimation de la variance, dans un modèle classique, si les coefficients d'aplatissement des variables sont connus
Estimation de moyennes et fonctions de répartition de suites d'échantillonnage
Estimation de Yule–Walker d'un CAR(p) observé à temps discret
Estimation des densités : risque minimax
Estimation des paramètres dans le modèle linéaire général dynamique
Estimation des paramètres d'un modèle de Rasch mixte par la méthode GEE : application en qualité de vie
Estimation du support et du contour du support d'une loi de probabilité
Estimation fonctionnelle. Risque minimax
Estimation for heavy tailed moving average process
In this paper, we propose two estimators for a heavy tailed MA(1) process. The first is a semi parametric estimator designed for MA(1) driven by positive-value stable variables innovations. We study its asymptotic normality and finite sample performance. We compare the behavior of this estimator in which we use the Hill estimator for the extreme index and the estimator in which we use the t-Hill in order to examine its robustness. The second estimator is for MA(1) driven by stable variables innovations...