Model selection in regression based on pre-smoothing

References

• Agresti , A. 2002 . Categorical Data Analysis , New York : Wiley .
   Google Scholar
• Akaike , H. Information theory and an extension of the maximum likelihood principle . In 2nd International Symposium on Information Theory . Edited by: Csaki , F. and Petrov , B. N. pp. 267 – 281 . Budapest : Akademia Kiado .
   Google Scholar
• Anderson , R. M. and May , R. M. 1991 . Infectious Diseases of Humans, Dynamic and Control , New York : Oxford University Press Inc .
   Google Scholar
• Beutels , M. , Van Damme , P. , Aelvoet , W. , Desmyter , J. , Dondeyne , F. , Goilav , C. , Mak , R. , Muylle , L. , Pierard , D. , Stroobant , A. , Van Loock , F. , Waumans , P. and Vranckx , R. 1997 . Prevalence of Hepatitis A, B and C in the Flemish population . Eur. J. Epidemiol. , 13 : 275 – 280 .
   PubMed Web of Science ®Google Scholar
• Burnham , K. P. and Anderson , D. R. 2002 . Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach , New York : Springer-Verlag .
   Google Scholar
• Christóbal Christóbal , J. A. , Faraldo Roca , P. and González Manteiga , W. 1987 . A class of linear regression parameter estimators constructed by nonparametric estimation . Ann. Statist., , 15 : 603 – 609 .
   Web of Science ®Google Scholar
• Efron , B. and Tibshirani , R. J. 1998 . An Introduction to the Bootstrap , Boca Raton : Chapman & Hall, CRC .
   Google Scholar
• Eilers , P. H.C. and Marx , B. D. 1996 . Flexible smoothing with B-splines and penalties (with discussion) . Statist. Sci. , 11 : 89 – 121 .
   Web of Science ®Google Scholar
• Faraldo Roca , P. and González Manteiga , W. 1987 . “ On efficiency of a new class of linear regression estimates obtained by preliminary nonparametric estimation ” . In New Perspectives in Theoretical and Applied Statistics , 229 – 242 . New York : Wiley .
   Google Scholar
• Gu , C. and Wahba , G. 1991 . Minimizing GCV/GML scores with multiple smoothing parameters via the Newton method . SIAM J. Sci. Stat. Comput. , 12 : 383 – 398 .
   Web of Science ®Google Scholar
• Hadler , S. C. “ Global impact of hepatitis A virus infection: changing patterns ” . In Viral Hepatitis and Liver Disease , Edited by: Hollinger , F. B. , Lemon , S. M. and Margolis , H. S. 14 – 20 . Baltimore : Williams & Wilkins .
   Google Scholar
• Hastie , T. J. and Tibshirani , R. J. 1990 . Generalized Additive Models , London : Chapman and Hall .
   Google Scholar
• Hens , N. , Aerts , M. and Molenberghs , G. 2006 . Model selection for incomplete and design-based samples . Stat. Med. , 25 : 2502 – 2520 .
   PubMed Web of Science ®Google Scholar
• Hoeting , J. , Raftery , A. E. and Madigan , D. 1996 . A method for simultaneous variable selection and outlier identification in linear regression . Comput. Statist. Data Anal. , 22 : 252 – 270 .
   Web of Science ®Google Scholar
• Hurvich , C. M. , Simonoff , J. S. and Tsai , C.-L. 1998 . Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion . JRSS-B , 60 : 271 – 293 .
   Google Scholar
• Janssen , P. , Swanepoel , J. and Veraverbeke , N. 2001 . Efficiency of linear regression estimators based on presmoothing . Comm. Statist. A , 30 : 2079 – 2097 .
   Google Scholar
• Kim , S. , Park , S. H. and Krzanowski , W. J. 2008 . Simultaneous variable selection and outlier identification in linear regression using the mean-shift outlier model . J. Appl. Stat. , 35 : 283 – 291 .
   Web of Science ®Google Scholar
• McQuarrie , A. D.R. and Tsai , C.-L. 1998 . Regression and Time Series Model Selection , Singapore : World Scientific .
   Google Scholar
• Opsomer , J. , Wang , Y. and Yang , Y. 2001 . Nonparametric regression with correlated errors . Statist. Sci. , 16 : 134 – 153 .
   Web of Science ®Google Scholar
• Pan , W. 2001 . Akaike's information criterion in generalized estimating equations . Biometrics , 57 : 120 – 125 .
   PubMed Web of Science ®Google Scholar
• Pan , W. 2001 . Model selection in estimating equations . Biometrics , 57 : 529 – 534 .
   PubMed Web of Science ®Google Scholar
• Royston , P. and Altman , D. 1994 . Regression using fractional polynomials of continuous covariates: Parsimonious parametric modeling . Appl. Statist. , 43 : 429 – 467 .
   Web of Science ®Google Scholar
• Ruppert , D. , Wand , M. P. and Carroll , R. J. 2003 . Semiparametric Regression , Cambridge : Cambridge University Press .
   Google Scholar
• Schwarz , G. 1978 . Estimating the dimension of a model . Ann. Statist. , 6 : 461 – 464 .
   Web of Science ®Google Scholar
• Shkedy , Z. , Aerts , M. , Molenberghs , M. , Beutels , Ph. and Van Damme , P. 2006 . Modeling age dependent force of infection from prevalence data using fractional polynomials . Stat. Med. , 25 : 1577 – 1591 .
   PubMed Web of Science ®Google Scholar
• Simonoff , J. S. 1996 . Smoothing Methods in Statistics , New York : Springer-Verlag .
   Google Scholar
• Simonoff , J. S. 2003 . Analyzing Categorical Data , New York : Springer-Verlag .
   Google Scholar
• Spiegelhalter , D. J. , Best , N. G. , Carlin , B. P. and van der Linde , A. 2002 . Bayesian measures of model complexity and fit . JRSS-B , 64 : 583 – 639 .
   Google Scholar
• Takeuchi , K. 1976 . Discussion of informational statistics and a criterion for model fitting . SuriKagaku , 153 : 12 – 18 .
   Google Scholar
• Wood , S. N. and Augustin , N. H. 2002 . GAMs with integrated model selection using penalized regression splines and applications to environmental modeling . Ecol. Model. , 157 : 157 – 177 .
   Web of Science ®Google Scholar
• Ye , J. 1998 . On measuring and correcting the effects of data mining and model selection . J. Amer. Statist. Assoc. , 93 : 120 – 131 .
   Web of Science ®Google Scholar