On the principle of equivariance: concepts and applications.
On the relationship between regression analysis and mathematical programming.
On the robustness of multiple regression coefficient estimators obtained by the p-point method
On the uniqueness of the M. L. estimates in curved exponential families
On variance of the two-stage estimator in variance-covariance components model
The paper deals with a linear model with linear variance-covariance structure, where the linear function of the parameter of expectation is to be estimated. The two-stage estimator is based on the observation of the vector and on the invariant quadratic estimator of the variance-covariance components. Under the assumption of symmetry of the distribution and existence of finite moments up to the tenth order, an approach to determining the upper bound for the difference in variances of the estimators...
On variance-covariance components estimation in linear models with AR(1) disturbances.
One Case of Reduction of Nonlinear Regression to Linear
One multivariate linear model with nuisance parameters
One of the calibration problems
One singular multivariate linear model with nuisance parameters
The multivariate linear model, in which the matrix of the first order parameters is divided into two matrices: to the matrix of the useful parameters and to the matrix of the nuisance parameters, is considered.
One-sided approximation of Bayes rule and its application to regression model with Cauchy noise
Optimal elimination of nuisance parameters in mixed linear models
Optimal Extrapolation of Derivatives.
Optimal L_p approximation techniques and data analysis
Optimal Regression Designs for Prediction when Prior Knowledge is Available.
Optimal stopping of a risk process
Optimal stopping time problems for a risk process where the number N(t) of losses up to time t is a general renewal process and the sequence of ’s represents successive losses are studied. N(t) and ’s are independent. Our goal is to maximize the expected return before the ruin time. The main results are closely related to those obtained by Boshuizen and Gouweleew [2].
Optimale Planung eines Kovarianzanalyse- und eines Intraclass Regressions-Experiments.
Optimale Versuchspläne bei zweifach klassifizierten Beobachtungsmodellen
Optimality of Balanced Designs for Minimum Norm Quadratic Unbiased Estimation of Variance Components.
Optimality of the least weighted squares estimator
The present paper deals with least weighted squares estimator which is a robust estimator and it generalizes classical least trimmed squares. We will prove -consistency and asymptotic normality for any sequence of roots of normal equation for location model. The influence function for general case is calculated. Finally optimality of this estimator is discussed and formula for most B-robust and most V-robust weights is derived.