[1] |
James W. Hardin and Joseph Hilbe.
Generalized Linear Models and Extensions.
College Station, Texas: Stata Press, 2001. [ bib ] |
[2] |
Kathryn Prewitt and Sharon Lohr.
Condition indices and bandwidth selection.
2003. [ bib ] |
[3] |
John M. Chambers and Trevor Hastie, editors.
Statistical models in S.
London: Chapman & Hall, 1991. [ bib ] |
[4] |
Clive Loader.
Local regression and likelihood.
New York: Springer-Verlag, 1999. [ bib ] |
[5] |
T. J. Hastie and R. J. Tibshirani.
Generalized additive models.
London: Chapman & Hall, 1990. [ bib ]
Keywords: Regression; Nonparametric; Generalized linear model |
[6] |
Robert Tibshirani and Trevor Hastie.
Local likelihood estimation.
Journal of the American Statistical Association, 82:559-567,
1987. [ bib ]
Keywords: Smoothing; Generalized linear model; Nonparametric regression |
[7] |
Trevor Hastie and Robert Tibshirani.
Generalized additive models.
Statistical Science, 1:297-310, 1986. [ bib ]
Keywords: Generalized linear model; Smoothing; Nonparametric regression; Partial residual; Nonlinear |
[8] |
Trevor Hastie and Robert Tibshirani.
Generalized additive models: Some applications.
Journal of the American Statistical Association, 82:371-386,
1987. [ bib ]
Keywords: Generalized linear model; Nonparametric regression; Logistic regression |
[9] |
Trevor Hastie and Clive Loader.
Local regression: Automatic kernel carpentry.
Statistical Science, 8:120-129, 1993. [ bib ]
Keywords: Loess; Smoothing |
[10] |
P. J. Green.
Iteratively reweighted least squares for maximum likelihood
estimation, and some robust and resistant alternatives (with discussion).
Journal of the Royal Statistical Society, Series B,
Methodological, 46:149-192, 1984. [ bib ]
Keywords: Scoring; Generalized linear model; Regression; Residual |
[11] |
William S. Cleveland and Susan J. Devlin.
Locally weighted regression: An approach to regression analysis by
local fitting.
Journal of the American Statistical Association, 83:596-610,
1988. [ bib ]
Keywords: Smoothing; Loess |
[12] |
William S. Cleveland.
Robust locally weighted regression and smoothing scatterplots.
Journal of the American Statistical Association, 74:829-836,
1979. [ bib ]
Keywords: Graphics; Nonparametric regression |
[13] |
J. A. Nelder and R. W. M. Wedderburn.
Generalized linear models.
Journal of the Royal Statistical Society, Series A, General,
135:370-384, 1972. [ bib ]
Keywords: Probit analysis; Analysis of variance; Contingency table; Exponential family; Quantal response; Weighted least squares |
[14] |
P. McCullagh and J. A. Nelder.
Generalized linear models (Second edition).
London: Chapman & Hall, 1989. [ bib ] |
[15] |
Andreas Buja, Trevor Hastie, and Robert Tibshirani.
Linear smoothers and additive models.
The Annals of Statistics, 17:453-510, 1989. [ bib ]
Keywords: Nonparametric; Regression; Kernel estimator |
[16] |
Jerome H. Friedman and Werner Stuetzle.
Projection pursuit regression.
Journal of the American Statistical Association, 76:817-823,
1981. [ bib ]
Keywords: Nonparametric regression; Smoothing |
[17] |
Jerome H. Friedman, Werner Stuetzle, and Anne Schroeder.
Projection pursuit density estimation.
Journal of the American Statistical Association, 79:599-608,
1984. [ bib ]
Keywords: Nonparametric |
[18] |
Leo Breiman and Jerome H. Friedman.
Estimating optimal transformations for multiple regression.
In Computer Science and Statistics: Proceedings of the 16th
Symposium on the Interface, pages 121-134, 1985. [ bib ]
Keywords: Nonparametric |
[19] |
Trevor Hastie, Robert Tibshirani, and J. H. Friedman.
The elements of statistical learning: data mining, inference,
and prediction: with 200 full-color illustrations.
New York: Springer-Verlag, 2001. [ bib ] |
[20] |
Charles J. Stone.
Optimal global rates of convergence for nonparametric regression.
The Annals of Statistics, 10:1040-1053, 1982. [ bib ] |
[21] |
Charles J. Stone.
Optimal rates of convergence for nonparametric estimators.
The Annals of Statistics, 8:1348-1360, 1980. [ bib ]
Keywords: Regression; Density estimation |
[22] |
Charles J. Stone.
Consistent nonparametric regression.
The Annals of Statistics, 5:595-620, 1977. [ bib ]
Keywords: Conditional quantities; prediction; Multiple classification; Bayes risk; Approximate Bayes rules; Nearest neighbor |
[23] |
Jianqing Fan.
Design-adaptive nonparametric regression.
Journal of the American Statistical Association, 87:998-1004,
1992. [ bib ]
Keywords: Smoothing |
[24] |
Jianqing Fan and Ir¨¨ne Gijbels.
Variable bandwidth and local linear regression smoothers.
The Annals of Statistics, 20:2008-2036, 1992. [ bib ] |
[25] |
Jianqing Fan.
Local linear regression smoothers and their minimax efficiencies.
The Annals of Statistics, 21:196-216, 1993. [ bib ]
Keywords: Nonparametric regression |
[26] |
Jianqing Fan and Ir¨¨ne Gijbels.
Data-driven bandwidth selection in local polynomial fitting:
Variable bandwidth and spatial adaptation.
Journal of the Royal Statistical Society, Series B,
Methodological, 57:371-394, 1995. [ bib ]
Keywords: Regression; Weighted least squares |
[27] |
Byeong U. Park and J. S. Marron.
Comparison of data-driven bandwidth selectors.
Journal of the American Statistical Association, 85:66-72,
1990. [ bib ]
Keywords: Density estimation; Kernel estimator |
[28] |
Peter Hall, Simon J. Sheather, M. C. Jones, and J. S. Marron.
On optimal data-based bandwidth selection in kernel density
estimation.
Biometrika, 78:263-269, 1991. [ bib ]
Keywords: Smoothing |
[29] |
S. J. Sheather and M. C. Jones.
A reliable data-based bandwidth selection method for kernel density
estimation.
Journal of the Royal Statistical Society, Series B,
Methodological, 53:683-690, 1991. [ bib ] |
[30] |
D. Ruppert, S. J. Sheather, and M. P. Wand.
An effective bandwidth selector for local least squares regression
(Corr: 96V91 p1380).
Journal of the American Statistical Association, 90:1257-1270,
1995. [ bib ]
Keywords: Kernel estimator; Variance estimation |
[31] |
M. C. Jones, J. S. Marron, and S. J. Sheather.
A brief survey of bandwidth selection for density estimation.
Journal of the American Statistical Association, 91:401-407,
1996. [ bib ]
Keywords: Review Paper; Kernel estimation; Nonparametric estimation; Smoothing; Bandwidth selection; Kernel density estimation; Nonparametric curve estimation; Smoothing parameter selection |
[32] |
Julia E. Kelsall and Peter J. Diggle.
Spatial variation in risk of disease: A nonparametric binary
regression approach.
Applied Statistics, 47:559-573, 1998. [ bib ]
Keywords: Cross-validation; Epidemiology; Kernel smoothing |
[33] |
Julia E. Kelsall and Peter J. Diggle.
Correction to ``Spatial variation in risk of disease: A
nonparametric binary regression approach'' (1998V47 p559-573).
Applied Statistics, 51(3):373-373, 2002. [ bib ] |
[34] |
D. Ruppert and M. P. Wand.
Multivariate locally weighted least squares regression.
The Annals of Statistics, 22:1346-1370, 1994. [ bib ]
Keywords: Kernel estimator; Nonparametric regression |
[35] |
Theo Gasser, Alois Kneip, and Walter Köhler.
A flexible and fast method for automatic smoothing.
Journal of the American Statistical Association, 86:643-652,
1991. [ bib ]
Keywords: Bandwidth; Kernel estimator |
[36] |
Burkhardt Seifert and Theo Gasser.
Finite-sample variance of local polynomials: Analysis and
solutions.
Journal of the American Statistical Association, 91:267-275,
1996. [ bib ]
Keywords: Theory and Methods; Nonparametric estimation; Nonparametric regression; Ridge regression; Smoothing; Weight function |
[37] |
E. A. Nadaraya.
On estimating regression.
Theory of Probability and its Applications, 9:141-142, 1964. [ bib ]
Keywords: Asymptotics |
[38] |
Geoffrey S. Watson.
Smooth regression analysis.
Sankhya Ser., 26:359-372, 1964. [ bib ]
Keywords: |
[39] |
Theo Gasser and Hans-Georg Müller.
Estimating regression functions and their derivatives by the kernel
method.
Scandinavian Journal of Statistics, 11:171-185, 1984. [ bib ]
Keywords: Nonparametric regression |