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 L_p approximation techniques and data analysis
Optimal Regression Designs for Prediction when Prior Knowledge is Available.
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.
Optimization of parameters in the Menzerath–Altmann law
Four formulas of the Menzerath–Altmann law are tested from the point of view of their applicability and suitability. The accuracy of related approximations of measured data is examined by the least square method at first. Then the accuracy of calculated parameters in the formulas under consideration is compared statistically. The influence of neglecting parameter is investigated as well. Finally, the obtained results are discussed by means of an illustrative example from quantitative linguistics....
Optimization of Parameters in the Menzerath–Altmann Law, II
The paper continues our studies released under the same title [Andres, J., Kubáček, L., Machalová, J., Tučková, M.: Optimization of parameters in the Menzerath–Altmann law Acta Univ. Palacki. Olomuc., Fac. rer. nat., Math. 51, 1 (2012), 5–27.]. As the main result justifying the conclusions in [Andres, J., Kubáček, L., Machalová, J., Tučková, M.: Optimization of parameters in the Menzerath–Altmann law Acta Univ. Palacki. Olomuc., Fac. rer. nat., Math. 51, 1 (2012), 5–27.], the theorem is presented...
Optimization of the size of nonsensitiveness regions
The problem is to determine the optimum size of nonsensitiveness regions for the level of statistical tests. This is closely connected with the problem of the distribution of quadratic forms.
Optimum experimental designs with a lack of a priori information. I. Designs for the estimation of a finite-dimensional set of functionals
Optimum experimental designs with a lack of a priori information. II. Designs for the estimation of the whole response function
Outliers in models with constraints
Outliers in univariate and multivariate regression models with constraints are under consideration. The covariance matrix is assumed either to be known or to be known only partially.
Overview of Recent Results in Growth-curve-type Multivariate Linear Models
The Extended Growth Curve Model (ECGM) is a multivariate linear model connecting different multivariate regression models in sample subgroups through common variance matrix. It has the form: Here, matrices contain subgroup division indicators, and corresponding regressors. If , we speak about (ordinary) Growth Curve Model. The model has already its age (it dates back to 1964), but it has many important applications. That is why it is still intensively studied. Many articles investigating...