Time-variant nonparametric extreme quantile estimation with application to US temperature data

[1]  B. Silverman,et al.  Nonparametric Regression and Generalized Linear Models: A roughness penalty approach , 1993 .

[2]  B. Silverman.  Density estimation for statistics and data analysis , 1986 .

[3]  I J Schoenberg,et al.  SPLINE FUNCTIONS AND THE PROBLEM OF GRADUATION. , 1964, Proceedings of the National Academy of Sciences of the United States of America.

[4]  G. Wahba.  Smoothing noisy data with spline functions , 1975 .

[5]  D. W. Scott,et al.  Multivariate Density Estimation, Theory, Practice and Visualization , 1992 .

[6]  C. J. Stone,et al.  Optimal Global Rates of Convergence for Nonparametric Regression , 1982 .

[7]  David W. Scott,et al.  Multivariate Density Estimation: Theory, Practice, and Visualization , 1992, Wiley Series in Probability and Statistics.

[8]  G. S. Watson,et al.  Smooth regression analysis , 1964 .

[9]  Jianqing Fan.  Design-adaptive Nonparametric Regression , 1992 .

[10]  Jianqing Fan,et al.  Local polynomial modelling and its applications , 1994 .

[11]  Jianqing Fan,et al.  Two‐step estimation of functional linear models with applications to longitudinal data , 1999 .

[12]  E. Nadaraya.  On Estimating Regression , 1964 .

[13]  M. Chowdhury.  Nonparametric Estimation of Time-Variant Parametric Models with Application to Cross-Sectional Data , 2017 .

[14]  I. J. Schoenberg,et al.  SPLINE FUNCTIONS AND THE PROBLEM OF GRADUATION , 1964 .

[15]  B. Silverman,et al.  Nonparametric regression and generalized linear models , 1994 .

[16]  Colin O. Wu,et al.  Nonparametric estimation of conditional distribution functions with longitudinal data and time-varying parametric models , 2018 .

[17]  W. Cleveland.  Robust Locally Weighted Regression and Smoothing Scatterplots , 1979 .

[18]  Li Ping Yang,et al.  Nonparametric smoothing estimates of time-varying coefficient models with longitudinal data , 1998 .

[19]  B. Silverman,et al.  Some Aspects of the Spline Smoothing Approach to Non‐Parametric Regression Curve Fitting , 1985 .

[20]  R. Koenker,et al.  Regression Quantiles , 2007 .

[21]  Bernard W. Silverman,et al.  Density Estimation for Statistics and Data Analysis , 1987 .

[22]  J. Hart,et al.  Kernel Regression Estimation Using Repeated Measurements Data , 1986 .

[23]  Grace Wahba,et al.  Spline Models for Observational Data , 1990 .

[24]  Jianqing Fan,et al.  Variable Bandwidth and Local Linear Regression Smoothers , 1992 .

[25]  Eric R. Ziegel,et al.  The Elements of Statistical Learning , 2003, Technometrics.

[26]  C. J. Stone,et al.  Optimal Rates of Convergence for Nonparametric Estimators , 1980 .

[27]  Colin O. Wu,et al.  Local Box–Cox transformation on time-varying parametric models for smoothing estimation of conditional CDF with longitudinal data , 2017 .

[28]  R. Eubank.  Nonparametric Regression and Spline Smoothing , 1999 .

[29]  Victor Solo.  Selection of regularisation parameters for total variation denoising , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[30]  Jianqing Fan.  Local Linear Regression Smoothers and Their Minimax Efficiencies , 1993 .

[31]  M. Wand,et al.  Multivariate Locally Weighted Least Squares Regression , 1994 .

[32]  C. J. Stone,et al.  Consistent Nonparametric Regression , 1977 .

[33]  C. Reinsch.  Smoothing by spline functions , 1967 .