Error analysis of a pairwise summation algorithm to compute the sample variance.
Estimación de registros desconocidos en series de datos.
Se dispone de dos o más series de datos, de las cuales al menos una no se conoce completamente. Se supone que las series se pueden modelizar con la hipótesis lineal; así como que existe alguna estructura de correlación entre ellas. Se desarrollan dos modelos para estimar los valores desconocidos de la(s) serie(s) de datos.
Estimateurs à rétrécisseurs de la moyenne d'une loi normale multidimensionnelle, pour un coût quadratique général
Estimating Regression Coefficients from Survey Data by Asymptotic Desingn-Cum-Model Based Approach.
Estimating the dimension of a linear model
Estimation and experimental design in a linear regression model using prior information
Estimation and prediction in regression models with random explanatory variables [Book]
Estimation de certaines interactions en analyse de variance
Estimation des paramètres d'un modèle de Rasch mixte par la méthode GEE : application en qualité de vie
Estimation in a special structure of the linear model
Estimation in autoregressive model with measurement error
Consider an autoregressive model with measurement error: we observe Zi = Xi + εi, where the unobserved Xi is a stationary solution of the autoregressive equation Xi = gθ0(Xi − 1) + ξi. The regression function gθ0 is known up to a finite dimensional parameter θ0 to be estimated. The distributions of ξ1 and X0 are unknown and gθ belongs to a large class of parametric regression functions. The distribution of ε0is completely known. We propose an estimation procedure with a new criterion computed as...
Estimation in connecting measurements with constraints of type II
This paper is a continuation of the paper [6]. It dealt with parameter estimation in connecting two–stage measurements with constraints of type I. Unlike the paper [6], the current paper is concerned with a model with additional constraints of type II binding parameters of both stages. The article is devoted primarily to the computational aspects of algorithms published in [5] and its aim is to show the power of -optimum estimators. The aim of the paper is to contribute to a numerical solution...
Estimation in multiepoch regression models with different structures for studying recent crustal movements
Estimation in universal models with restrictions
In modelling a measurement experiment some singularities can occur even if the experiment is quite standard and simple. Such an experiment is described in the paper as a motivation example. It is presented in the papar how to solve these situations under special restrictions on model parameters. The estimability of model parameters is studied and unbiased estimators are given in explicit forms.
Estimation non paramétrique de la régression par la méthode du noyau : propriété de convergence asymptotiquememt normale indépendante
Estimation non-paramétrique par noyaux : régression polynomiale mobile
Estimation of a quadratic function of the parameter of the mean in a linear model
The paper deals with an optimal estimation of the quadratic function , where is a known matrix, in the model . The distribution of is assumed to be symmetric and to have a finite fourth moment. An explicit form of the best unbiased estimator is given for a special case of the matrix .
Estimation of a Regression Coefficient After two Preliminary Tests of Significance.
Estimation of covariance components in a repeated regression experiment
Estimation of dispersion in nonlinear regression models with constraints
Dispersion of measurement results is an important parameter that enables us not only to characterize not only accuracy of measurement but enables us also to construct confidence regions and to test statistical hypotheses. In nonlinear regression model the estimator of dispersion is influenced by a curvature of the manifold of the mean value of the observation vector. The aim of the paper is to find the way how to determine a tolerable level of this curvature.