Data imputation in switchback designs using a mixed model with correlated errors.
Decomposing matrices with Jerzy K. Baksalary
In this paper we comment on some papers written by Jerzy K. Baksalary. In particular, we draw attention to the development process of some specific research ideas and papers now that some time, more than 15 years, has gone after their publication.
Densities of determinant ratios, their moments and some simultaneous confidence intervals in the multivariate Gauss-Markoff model
The following three results for the general multivariate Gauss-Markoff model with a singular covariance matrix are given or indicated. determinant ratios as products of independent chi-square distributions, moments for the determinants and the method of obtaining approximate densities of the determinants.
Detection of influential points by convex hull volume minimization
A method of geometrical characterization of multidimensional data sets, including construction of the convex hull of the data and calculation of the volume of the convex hull, is described. This technique, together with the concept of minimum convex hull volume, can be used for detection of influential points or outliers in multiple linear regression. An approximation to the true concept is achieved by ordering the data into a linear sequence such that the volume of the convex hull of the first...
Deux méthodes linéaires en statistique multidimensionnelle (1). A. - Introduction aux deux méthodes. B. - Analyse en composantes principales
Dans deux articles, dont voici le premier, sont présentés deux exemples d'analyse statistique par des méthodes factorielles. Le cadre mathématique de l'exposé est algébrique. La présente formulation de ces problèmes s'appuie sur l'expérience d'enseignement menée à l'UER de Mathématiques, Logique Formelle et Informatique de l'Université René-Descartes, ainsi que sur une rédaction parue dans les actes du Colloque «Analyse des données en architecture et urbanisme» [5].
Deux structures statistiques fondamentales en analyse de la variance univariée et multivariée
Die Nichtkonsistenz der M.-L. Schätzer im Â?Switching Regression" Problem.
Different kinds of sufficiency in the general Gauss-Markov model
Directional quantile regression in Octave (and MATLAB)
Although many words have been written about two recent directional (regression) quantile concepts, their applications, and the algorithms for computing associated (regression) quantile regions, their software implementation is still not widely available, which, of course, severely hinders the dissemination of both methods. Wanting to partly fill in the gap here, we provide all the codes needed for computing and plotting the multivariate (regression) quantile regions in Octave and MATLAB, describe...
Directional quantile regression in R
Recently, the eminently popular standard quantile regression has been generalized to the multiple-output regression setup by means of directional regression quantiles in two rather interrelated ways. Unfortunately, they lead to complicated optimization problems involving parametric programming, and this may be the main obstacle standing in the way of their wide dissemination. The presented R package modQR is intended to address this issue. It originates as a quite faithful translation of the authors'...
Distribution of estimators and optimal experimental design in nonlinear regression
Distribution of the weighted L.S. estimates in nonlinear models with symmetrical errors
Dynamics of an artificial slope
The slope shape is replaced by a 3D regression function which corresponds with high precision to the position of several hundred points which were determined on the surface of the slope body. The position of several points was repeatedly measured for several years. The time changes in the position of these points were used to create regression functions that describe vertical movements, slope settlement and horizontal movements, slope movement. The model results are presented in the form of mathematical...