L. Kubacek, Department of Mathematical Analysis and Applied Mathematics, Faculty of Science, Palacky University, Tomkova 40, 779 00 Olomouc, Czech Republic, e-mail: kubacekl@risc.upol.cz
Abstract: In nonlinear regression models with constraints a linearization of the model leads to a bias in estimators of parameters of the mean value of the observation vector. Some criteria how to recognize whether a linearization is possible is developed. In the case that they are not satisfied, it is necessary to decide whether some quadratic corrections can make the estimator better. The aim of the paper is to contribute to the solution of the problem.
Keywords: nonlinear regression model with constraints, linearization, quadratization
Classification (MSC 2000): 62J05, 62F10
Full text available as PDF (smallest), as compressed PostScript (.ps.gz) or as raw PostScript (.ps).
Access to the full text of journal articles on this site is restricted to the subscribers of Myris Trade.
To activate your access, please contact Myris Trade at myris@myris.cz.
Subscribers of Springer (formerly Kluwer) need to access the articles on their site, which is http://www.springeronline.com/10492.
