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2007 | 17 | 2 | 179-187
Tytuł artykułu

Iterative estimators of parameters in linear models with partially variant coefficients

Treść / Zawartość
Warianty tytułu
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.
Rocznik
Tom
17
Numer
2
Strony
179-187
Opis fizyczny
Daty
wydano
2007
poprawiono
2006-05-10
(nieznana)
2006-12-15
Twórcy
autor
  • Nanjing University of Science and Technology, 210071, Nanjing, China
autor
  • Department of Computer Science, Royal Institute of Technology, Stockholm, 100-44, Sweden
autor
  • Nanjing University of Science and Technology, 210071, Nanjing, China
  • University of Liverpool, L69 3 GH, Liverpool, United Kingdom
Bibliografia
  • 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
  • Dodge Y. and Kova J. (2000): Adaptive Regression. - Berlin: Springer.
  • Draper N.R. and Smith H. (1981): Applied Regression Analysis. - New York: Wiley.
  • 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.
  • Fahrmeier L. and Tutz G.(2001): Multivariate Statistical Modeling Based on Generalized Linear Models. - Berlin: Springer.
  • Frank E. and Harrell J.(2002): Regression Modeling Strategies with Applications to Linear Models, Logistic Regression, and Survival Analysis. - New York: Springer.
  • Graybill F.A. and Iyer H.K. (1994): Regression Analysis: Concepts and Applications. - Massachusetts: Duxbury Press.
  • Hu Shaolin and Sun Guoji (2001): Process Monitoring Technique and Applications. - Bejing: National Defense Industry Press.
  • 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.
  • Rencher A. (2000): Linear Models in Statistics. - New York: Wiley
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.bwnjournal-article-amcv17i2p179bwm
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