Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
The paper is devoted to the problem of a choice between various regression estimators in real world applications. We emphasise the role of cross-validation techniques when doing such a choice in actual usage, especially in the situations where theoretical assumption about considered problem are difficult to verify and the aim of the model building is the prediction of future values of the response variable.
Słowa kluczowe
Rocznik
Tom
Strony
39--44
Opis fizyczny
Bibliogr. 7 poz., tab.
Twórcy
autor
- Institute of Mathematics and Computer Science, Czestochowa University of Technology
Bibliografia
- [1] Berger J.O., Statistical Decision Theory and Bayesian Analysis, Springer Verlag, New York 1985.
- [2] Birkes D., Dodge Y., Alternative methods of regression, Wiley & Sons, New York 1993.
- [3] Frees E.W., Data analysis using regression models - the business perspective, Prentice-Hall Inc., New Jersey 1996.
- [4] Grzybowski A., Metody wykorzystania informacji a priori w estymacji parametrów regresji, Wydawnictwo Politechniki Częstochowskiej, Częstochowa 2002, seria monografie.
- [5] Kohavi R., A study of cross-validation and bootstrap for accuracy estimation and model selection, Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, San Mateo 1995, 1137-1143.
- [6] Plutowski M.E., Sakata S., White H., Cross-validation estimates integrated mean squared error, Giles C.L., Hanson S.J., Cowan J.D. (eds.), Advances in neural information processing systems 6, Morgan Kaufmann Publishers, San Mateo 1994.
- [7] Shao J., Linear model selection by cross-validation, Journal of the American Statistical Association 1993, 88, 422, 486-494.
Uwagi
EN
The papers have been presented during the session devoted to application of mathematics (as part of International Conference on Parallel Processing and Applied Mathematics).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c38a0c2d-75a8-4524-8ee2-4b5e93c96eac