Local Bandwidth Choice in Kernel Regression Estimation

References

• Brockmann , M. , Gasser , T. and Herrmann , E. 1993 . “Locally Adaptive Bandwidth Choice for Kernel Regression Estimators” . Journal of the American Statistical Association , 88 : 1302 – 1309 .
   Web of Science ®Google Scholar
• Chu , C. K. and Marron , J. S. 1991 . “Choosing a Kernel Regression Estimator” . Statistical Science , 6 : 404 – 436 .
   Google Scholar
• Donoho , D. L. and Johnstone , I. M. 1994 . “Ideal Spatial Adaptation by Wavelet Shrinkage” . Biometrika , 81 : 425 – 455 .
   Web of Science ®Google Scholar
• Donoho , D. L. , Johnstone , I. M. , Kerkyacharian , G. and Picard , D. 1995 . “Wavelet Shrinkage: Asymptopia?” . Journal of the Royal Statistical Society , 57 : 301 – 369 . Ser. B
   Google Scholar
• Fan , J. and Gijbels , I. 1995 . “Data-Driven Bandwidth Selection in Local Polynomial Fitting: Variable Bandwidth and Spatial Adaptation” . Journal of the Royal Statistical Society , 57 : 371 – 394 . Ser. B
   Google Scholar
• Fan , J. , Hall , P. , Martin , M. and Patil , P. 1996 . “On Local Smoothing of Nonparametric Curve Estimators” . Journal of the American Statistical Association , 91 : 258 – 266 .
   Web of Science ®Google Scholar
• Fan , J. and Marron , J. S. 1994 . “Fast Implementation of Nonparametric Curve Estimators” . Journal of Computational and Graphical Statistics , 3 : 35 – 56 .
   Google Scholar
• Gasser , T. and Kneip , A. 1989 . Discussion of “Linear Smoothers and Additive Models” . The Annals of Statistics , 17 : 532 – 535 . by A. Buja, T. Hastie, and R. Tibshirani
   Google Scholar
• Gasser , T. , Kneip , A. and Köhler , W. 1991 . “A Flexible and Fast Method for Automatic Smoothing” . Journal of the American Statistical Association , 86 : 643 – 652 .
   Web of Science ®Google Scholar
• Gasser , T. and Müller , H.-G. 1984 . “Estimating Regression Functions and Their Derivatives by the Kernel Method” . Scandinavian Journal of Statistics , 11 : 171 – 185 .
   Web of Science ®Google Scholar
• Gasser , T. , Müller , H.-G. and Mammitzsch , V. 1985 . “Kernels for Nonparametric Curve Estimation” . Journal of the Royal Statistical Society , 47 : 238 – 252 . Ser. B
   Google Scholar
• Gasser , T. , Sroka , L. and Jennen-Steinmetz , C. 1986 . “Residual Variance and Residual Pattern in Nonlinear Regression” . Biometrika , 73 : 625 – 633 .
   Web of Science ®Google Scholar
• Härdle , W. and Marron , J. S. 1985 . “Optimal Bandwidth Selection in Nonparametric Regression Function Estimation” . The Annals of Statistics , 13 : 1465 – 1482 .
   Web of Science ®Google Scholar
• Härdle , W. , Hall , P. and Marron , J. S. 1988 . “How Far are Automatically Chosen Regression Smoothing Parameters From Their Optimum?” . Journal of the American Statistical Association , 83 : 86 – 99 .
   Web of Science ®Google Scholar
• Härdle , W. , Hall , P. and Marron , J. S. 1992 . “Regression Smoothing Parameters That Are Not Far From Their Optimum” . Journal of the American Statistical Association , 87 : 227 – 233 .
   Web of Science ®Google Scholar
• Hall , P. , Kay , J. W. and Titterington , D. M. 1990 . “Asymptotically Optimal Difference Based Estimation of Variance in Nonparametric Regression” . Biometrika , 77 : 521 – 528 .
   Web of Science ®Google Scholar
• Hall , P. and Marron , J. S. 1990 . “On Variance Estimation in Nonparametric Regression” . Biometrika , 77 : 415 – 419 .
   Web of Science ®Google Scholar
• Herrmann , E. 1996 . “On the Convolution Type Kernel Regression Estimator” , Fachbereich Mathematik, Technische Hochschule Darmstadt . preprint
   Google Scholar
• Jones , M. C. , Davies , S. J. and Park , B. U. 1994 . “Versions of Kernel-Type Regression Estimators” . Journal of the American Statistical Association , 89 : 825 – 832 .
   Web of Science ®Google Scholar
• Mammen , E. and Gijbels , I. 1994 . “On Local Adaptivity of Kernel Estimates With Plug-In Local Bandwidth Selectors” unpublished manuscript
   Google Scholar
• Müller , H.-G. and Stadtmüller , U. 1987 . “Variable Bandwidth Kernel Estimators of Regression Curves” . The Annals of Statistics , 15 : 182 – 201 .
   Web of Science ®Google Scholar
• Rice , J. 1984 . “Bandwidth Choice for Nonparametric Kernel Regression” . The Annals of Statistics , 12 : 1215 – 1230 .
   Web of Science ®Google Scholar
• Ruppert , D. , Sheather , S. J. and Wand , M. P. 1995 . “An Effective Bandwidth Selector for Local Least Squares Regression” . Journal of the American Statistical Association , 90 : 1257 – 1270 .
   Web of Science ®Google Scholar
• Seifert , B. , Brockmann , M. , Engel , J. and Gasser , T. 1994 . “Fast Algorithms for Nonparametric Curve Estimation” . Journal of Computational and Graphical Statistics , 3 : 192 – 213 .
   Google Scholar
• Seifert , B. , Gasser , T. and Wolf , A. 1993 . “Nonparametric Estimation of Residual Variance Revisited” . Biometrika , 80 : 373 – 383 .
   Web of Science ®Google Scholar
• Sheather , S. J. and Jones , M. C. 1991 . “A Reliable Data-Based Bandwidth Selection Method for Kernel Density Estimation” . Journal of the Royal Statistical Society , 53 : 683 – 690 . Ser. B
   Google Scholar
• Staniswalis , J. G. 1989 . “Local Bandwidth Selection for Kernel Estimates” . Journal of the American Statistical Association , 84 : 284 – 287 .
   Web of Science ®Google Scholar
• Vieu , P. 1991 . “Nonparametric Regression: Optimal Local Bandwidth Choice” . Journal of the Royal Statistical Society , 53 : 453 – 464 . Ser. B
   Google Scholar