Iterative estimators of parameters in linear models with partially variant coefficients

• Autorzy: Hu S. , Meinke K. , Chen R. , Huajiang O.
• Języki publikacji: EN

Abstrakty

EN

A new kind of linear model with partially variant coefficients is proposed and a series of iterative algorithms are introduced and verified. The new generalized linear model includes the ordinary linear regression model as a special case. The iterative algorithms efficiently overcome some difficulties in computation with multidimensional inputs and incessantly appending parameters. An important application is described at the end of this article, which shows that this new model is reasonable and applicable in practical fields.

Słowa kluczowe

EN

linear model; parameter estimation; iterative algorithms; variant coefficients

PL

model liniowy; estymacja parametrów; algorytm iteracyjny; współczynnik zmienności

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2007
• Tom: Vol. 17, no 2
• Strony: 179--187
• Opis fizyczny: Bibliogr. 10 poz., tab.

Twórcy

autor

Hu S.

• Nanjing University of Science and Technology, 210071, Nanjing, China; Department of Computer Science, Royal Institute of Technology, Stockholm, 100-44, Sweden

autor

Meinke K.

• Department of Computer Science, Royal Institute of Technology, Stockholm, 100-44, Sweden

autor

Chen R.

• Nanjing University of Science and Technology, 210071, Nanjing, China

autor

Huajiang O.

• University of Liverpool, Liverpool, United Kingdom, L69 3 GH, Liverpool, UK

Bibliografia

• [1] Brown D.C. (1964): The Error Model Best Estimation Trajectory.- Tech. Rep. AD 602799: http://stinet.dtic.mil/oai/oai?&verb=getRecorg&metadataPrefix=html&identifier=AD0602799
• [2] Dodge Y. and Kova J. (2000): Adaptive Regression. - Berlin: Springer.
• [3] Draper N.R. and Smith H. (1981): Applied Regression Analysis. - New York: Wiley.
• [4] Eubank R., Chunfeng H., Maldonado Y., Naisyin W., Suojin W., Buchanan R.J. (2004): Smoothing spline estimation in varying coefficient models. - J. Roy. Stat. Soc. B, Vol. 66, No. 3, pp. 653-667.
• [5] Fahrmeier L. and Tutz G.(2001): Multivariate Statistical Modeling Based on Generalized Linear Models. - Berlin: Springer.
• [6] Frank E. and Harrell J.(2002): Regression Modeling Strategies with Applications to Linear Models, Logistic Regression, and Survival Analysis. -New York: Springer.
• [7] Graybill F.A. and Iyer H.K. (1994): Regression Analysis: Concepts and Applications. -Massachusetts: Duxbury Press.
• [8] Hu Shaolin and Sun Guoji (2001): Process Monitoring Technique and Applications. - Bejing: National Defense Industry Press.
• [9] Kala R. and Kłaczyński K. (1988): Recursive improvement of estimates in a Gauss-Markov model with linear restrictions. Canad. J. Stat., Vol. 16, No. 3, pp. 301-305.
• [10] Rencher A. (2000): Linear Models in Statistics. - New York: Wiley.