Nonparametric regression: An up–to–date bibliography

We attempt to give a complete list of references in non parametric regression estimation (including non parametric time series analysis), with a brief introduction of these works according a classification taking the diversity of problems or methods into account.

[1]  L. Devroye,et al.  Distribution-Free Consistency Results in Nonparametric Discrimination and Regression Function Estimation , 1980 .

[2]  Y. Mack,et al.  Local Properties of k-NN Regression Estimates , 1981 .

[3]  R. Singh.  Applications of Estimators of a Density and its Derivatives to Certain Statistical Problems , 1977 .

[4]  P. Cazes.  Régression par boule et par l'analyse des correspondances , 1976 .

[5]  M. Rosenblatt,et al.  Smoothing Splines: Regression, Derivatives and Deconvolution , 1983 .

[6]  R. M. Clark.  Non‐Parametric Estimation of a Smooth Regression Function , 1977 .

[7]  M. J. Fryer.  A Review of Some Non-parametric Methods of Density Estimation , 1977 .

[8]  Leszek Rutkowski,et al.  On system identification by nonparametric function fitting , 1982 .

[9]  G. Collomb.  Jfon parametric time series analysis and prediction: uniform almost sure convergence of the window and jt-nn autoregression estimates , 1985 .

[10]  A. Földes,et al.  STRONG UNIFORM CONSISTENCY FOR NONPARAMETRIC SURVIVAL CURVE ESTIMATORS FROM RANDOMLY CENSORED DATA , 1981 .

[11]  I. Ahmad,et al.  NONPARAMETRIC SEQUENTIAL ESTIMATION OF A MULTIPLE REGRESSION FUNCTION , 1976 .

[12]  B. Silverman,et al.  Weak and strong uniform consistency of kernel regression estimates , 1982 .

[13]  P. Révész,et al.  How to apply the method of stochastic approximation in the non-parametric estimation of a regression function 1 , 1977 .

[14]  P. Speckman.  Spline Smoothing and Optimal Rates of Convergence in Nonparametric Regression Models , 1985 .

[15]  P. Révész,et al.  Strong approximations in probability and statistics , 1981 .

[16]  S. Yakowitz,et al.  Contributions to the Theory of Nonparametric Regression, with Application to System Identification , 1979 .

[17]  L. Devroye.  Necessary and sufficient conditions for the pointwise convergence of nearest neighbor regression function estimates , 1982 .

[18]  H. Müller,et al.  Kernel estimation of regression functions , 1979 .

[19]  Peter E. Hart,et al.  Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.

[20]  S. Wold.  Spline Functions in Data Analysis , 1974 .

[21]  Edmund Taylor Whittaker.  On a New Method of Graduation , 1922, Proceedings of the Edinburgh Mathematical Society.

[22]  D. F. Utreras,et al.  Optimal Smoothing of Noisy Data Using Spline Functions , 1981 .

[23]  Prakasa Rao.  Nonparametric functional estimation , 1983 .

[24]  Stanley C. Fralick,et al.  Nonparametric Bayes-risk estimation , 1971, IEEE Trans. Inf. Theory.

[25]  H. Liero.  On the maximal deviation of the kernel regression function estimate , 1982 .

[26]  Robert F. Ling,et al.  Classification and Clustering. , 1979 .

[27]  P. Tuan.  Nonparametric estimation of the drift coefficient in the diffusion equation , 1981 .

[28]  W. S. Meisel,et al.  General Estimates of the Intrinsic Variability of Data in Nonlinear Regression Models , 1976 .

[29]  F. Utreras.  Cross-validation techniques for smoothing spline functions in one or two dimensions , 1979 .

[30]  I. A. Ibragimov,et al.  Bounds for the Risks of Non-Parametric Regression Estimates , 1982 .

[31]  John Van Ryzin,et al.  Classification and clustering : proceedings of an advanced seminar conducted by the Mathematics Research Center, the University of Wisconsin at Madison, May 3-5, 1976 , 1977 .

[32]  D. Bosq.  Sur la prédiction non paramétrique de variables aléatoires et de mesures aléatoires , 1983 .

[33]  G. Banon.  Nonparametric Identification for Diffusion Processes , 1978 .

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

[35]  G. Wahba,et al.  A completely automatic french curve: fitting spline functions by cross validation , 1975 .

[36]  E. Nadaraya.  A limit distribution of the square error deviation of nonparametric estimators of the regression function , 1983 .

[37]  M. Priestley,et al.  Non‐Parametric Function Fitting , 1972 .

[38]  A. Albert.  A Mathematical Theory of Pattern Recognition , 1963 .

[39]  E. Nadaraya.  On Non-Parametric Estimates of Density Functions and Regression Curves , 1965 .

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

[41]  Peter Craven,et al.  Smoothing noisy data with spline functions , 1978 .

[42]  A. Krzyżak,et al.  Distribution-Free Pointwise Consistency of Kernel Regression Estimate , 1984 .

[43]  L. Devroye.  The uniform convergence of the nadaraya‐watson regression function estimate , 1978 .

[44]  M. Rosenblatt.  Remarks on Some Nonparametric Estimates of a Density Function , 1956 .

[45]  V. Konakov.  On a Global Measure of Deviation for an Estimate of the Regression Line , 1978 .

[46]  G. Wahba,et al.  Some New Mathematical Methods for Variational Objective Analysis Using Splines and Cross Validation , 1980 .

[47]  T. Cacoullos,et al.  Discriminant analysis and applications , 1974 .

[48]  E. L. Lehmann,et al.  Unbiased Estimation in Convex Families , 1969 .

[49]  T. Teichmann,et al.  Harmonic Analysis and the Theory of Probability , 1957, The Mathematical Gazette.

[50]  E. Nadaraya,et al.  On the Integral Mean Square Error of Some Nonparametric Estimates for the Density Function , 1974 .

[51]  S. Yakowitz,et al.  Uniform Convergence of the Potential Function Algorithm , 1976 .

[52]  G. Collomb,et al.  From Data Analysis to Non Parametric Statistics: Recent Developments and a Computer Realization for Exploratory Techniques in Regression or Prediction , 1982 .

[53]  G. Collomb.  Propriétés de convergence presque complète du prédicteur à noyau , 1984 .

[54]  Eugene F. Schuster,et al.  Joint Asymptotic Distribution of the Estimated Regression Function at a Finite Number of Distinct Points , 1972 .

[55]  Jiří Akaeěl,et al.  Fitting models in time series analysis , 1982 .

[56]  C. J. Stone,et al.  Admissible Selection of an Accurate and Parsimonious Normal Linear Regression Model , 1981 .

[57]  József Fritz,et al.  Distribution-free exponential error bound for nearest neighbor pattern classification , 1975, IEEE Trans. Inf. Theory.

[58]  C. Spiegelman,et al.  Consistent Window Estimation in Nonparametric Regression , 1980 .

[59]  A CLASS OF NONPARAMETRIC RECURSIVE ESTIMATORS OF A MULTIPLE REGRESSION FUNCTION , 1983 .

[60]  V. Konakov.  Asymptotic properties of some functions of nonparametric estimates of a density function , 1973 .

[61]  Godfried T. Toussaint,et al.  Bibliography on estimation of misclassification , 1974, IEEE Trans. Inf. Theory.

[62]  G. Roussas.  Nonparametric Estimation of the Transition Distribution Function of a Markov Process , 1969 .

[63]  Leszek Rutkowski,et al.  ORTHOGONAL SERIES ESTIMATES OF A REGRESSION FUNCTION WITH APPLICATIONS IN SYSTEM IDENTIFICATION , 1982 .

[64]  F. Utreras Diaz,et al.  Sur le choix du paramètre d'ajustement dans le lissage par fonctions spline , 1980 .

[65]  Non Parametric Prediction in Stationary Processes , 1983 .

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

[67]  G. Wahba.  Bayesian "Confidence Intervals" for the Cross-validated Smoothing Spline , 1983 .

[68]  P. Newbold,et al.  Some Recent Developments in Time Series Analysis. III, Correspondent Paper , 1981 .

[69]  B. Silverman,et al.  Density Ratios, Empirical Likelihood and Cot Death , 1978 .

[70]  G. Wahba.  Improper Priors, Spline Smoothing and the Problem of Guarding Against Model Errors in Regression , 1978 .

[71]  L. Devroye,et al.  On the L1 convergence of kernel estimators of regression functions with applications in discrimination , 1980 .

[72]  Gérard Collomb,et al.  From Non Parametric Regression to Non Parametric Prediction: Survey of the Mean Square Error and Original Results on the Predictogram , 1983 .

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

[74]  G. R. Goel.  Limited space heterogeneous queueing problem with an additional special feeding source , 1977 .

[75]  H. Robbins.  The Empirical Bayes Approach to Statistical Decision Problems , 1964 .

[76]  C. Ansley,et al.  The Signal Extraction Approach to Nonlinear Regression and Spline Smoothing , 1983 .

[77]  W. Wertz.  Statistical density estimation: A survey , 1978 .

[78]  Gordon J Johnston,et al.  Probabilities of maximal deviations for nonparametric regression function estimates , 1982 .

[79]  Simulation in the General First Order Autoregressive Process (Unidimensional Normal Case) , 1983 .

[80]  Pratique de la régression : qualité et protection , 1975 .

[81]  J. V. Ryzin,et al.  On the Empirical Bayes Approach to Multiple Decision Problems , 1977 .

[82]  E. Nadaraya.  Remarks on Non-Parametric Estimates for Density Functions and Regression Curves , 1970 .

[83]  A. Krzyżak,et al.  Asymptotic properties of kernel estimates of a regression function , 1980 .

[84]  L. Rutkowski.  On-line identification of time-varying systems by nonparametric techniques , 1982 .

[85]  Pi-Erh Lin,et al.  Nonparametric estimation of a regression function , 1981 .

[86]  D. S. Tracy,et al.  Strongly consistent estimators of k-th order regression curves and rates of convergence , 1977 .

[87]  Remarks upon Empirical Regression Belt , 1979 .

[88]  Kazuo Noda,et al.  Estimation of a regression function by the parzen kernel-type density estimators , 1976 .

[89]  S. Yakowitz.  Nonparametric Estimation of Markov Transition Functions , 1979 .

[90]  A. Georgiev.  Speed of convergence in nonparametric kernel estimation of a regression function and its derivatives , 1984 .

[91]  G. Wahba.  A Comparison of GCV and GML for Choosing the Smoothing Parameter in the Generalized Spline Smoothing Problem , 1985 .

[92]  I. W. Wright.  Splines in Statistics , 1983 .

[93]  G. Collomb.  Estimation Non-paramétrique de la Régression: Revue Bibliographique@@@Estimation Non-parametrique de la Regression: Revue Bibliographique , 1981 .

[94]  G. Collomb.  Estimation de la regression par la methode des k points les plus proches avec noyau : quelques propriétés de convergence ponctuelle , 1980 .

[95]  A. Krzyżak,et al.  Almost Everywhere Convergence of Recursive Kernel Regression Function Estimates , 1982 .

[96]  L. Devroye.  On the Almost Everywhere Convergence of Nonparametric Regression Function Estimates , 1981 .

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

[98]  Thomas M. Cover,et al.  Estimation by the nearest neighbor rule , 1968, IEEE Trans. Inf. Theory.

[99]  J. Kiefer,et al.  Asymptotic Minimax Character of the Sample Distribution Function and of the Classical Multinomial Estimator , 1956 .

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

[101]  K. Pearson,et al.  ON THE LAWS OF INHERITANCE IN MAN I. INHERITANCE OF PHYSICAL CHARACTERS , 1903 .

[102]  G. Wahba.  Spline Interpolation and Smoothing on the Sphere , 1981 .

[103]  Luc Devroye,et al.  The uniform convergence of nearest neighbor regression function estimators and their application in optimization , 1978, IEEE Trans. Inf. Theory.

[104]  M. Goovaerts,et al.  On the infinite divisibility of the ratio of two gamma-distributed variables , 1978 .

[105]  Efficacités comparées de certaines méthodes de prédiction pour un ARMA perturbé , 1981 .

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