Nonparametric Functional Estimation and Related Topics

I. Curve and Functional Estimation.- Reproducing Kernels and Finite Order Kernels.- Laws of the Iterated Logaritm for Density Estimators.- Exponential Inequalities in Nonparametric Estimation.- Conservative Confidence Bands for Nonparametric Regression.- Data-Adaptive Kernel Estimation.- On the Nonparametric Estimation of the Entropy Functional.- II. Curve and Functional Estimation (Continued).- Analysis of Samples of Curves.- Bootstrap Methods in Nonparametric Regression.- On the Influence Function of Maximum Penalized Likelihood Density Estimators.- Nonparametric Curve Estimation and Simple Curve Characteristics.- Applications of Multiparameter Weak Convergence for Adaptive Nonparametric Curve Estimation.- On Asymptotic Efficiency of Average Derivative Estimates.- Nonparametric Estimation of Elliptically Contoured Densities.- Uniform Deconvolution: Nonparametric Maximum Likelihood and Inverse Estimation.- III. Parameter Selection, Smoothing.- Smoothing Parameter Selection in Image Restoration.- Estimating the Quantile-Density Function.- Data-Driven Smoothing Based on Convexity Properties.- Prospects for Automatic Bandwidth Selection in Extensions to Basic Kernel Density Estimation.- Root n Bandwidth Selection.- Estimating Smooth Distribution Functions.- Smoothing Techniques in Time Series Analysis.- IV. Regression Models.- Nonparametric Inference in Heteroskedastic Regression.- Bounded Influence Regression in the Presence of Heteroskedasticity of Unknown Form.- Linear Regression with Randomly Right-Censored Data Using Prior Nonparametric Estimation.- Universal Consistencies of a Regression Estimate for Unbounded Regression Functions.- Minimax Bayes Estimation, Penalized Likelihood Methods, and Restricted Minimax Estimation.- On Exponential Bounds on the Bayes Risk of the Nonparametric Classification Rules.- Nonparametric Regression Analysis of Some Economic Data.- V. Dependent Data.- Nonparametric Regression Methods for Repeated Measurements.- Nonparametric Prediction for Unbounded Almost Stationary Processes.- Monte Carlo and Turbulence.- Kernel Density Estimation Under a Locally Mixing Condition.- Nonparametric Estimation of Survival Functions Under Dependent Competing Risks.- Estimation of Transition Distribution Function and Its Quantiles in Markov Processes: Strong Consistency and Asymptotic Normality.- L1 Strong Consistency for Density Estimates in Dependent Samples.- VI. Time Series Analysis, Signal Detection.- Nonparametric Statistical Signal Detection Problems.- Functional Identification in Nonlinear Time Series.- Modelization, Nonparametric Estimation and Prediction for Continuous Time Processes.- Estimation of Chaotic Dynamic Systems with Control Variables.- Nonparametric Estimation of a Class of Nonlinear Time Series Models.- Semiparametric and Nonparametric Inference from Irregular Observations on Continuous Time Stochastic Processes.- VII. Various Topics.- Complexity Regularization with Application to Artificial Neural Networks.- Designing Prediction Bands.- Analysis of Observational Studies from the Point of View of Nonparametric Regression.- Some Issues in Cross-Validation.- Nonparametric Function Estimation Involving Errors-in-Variables.- VII. Various Topics (Continued).- A Consistent Goodness of Fit Test Based on the Total Variation Distance.- On a Problem in Semiparametric Estimation.- On the Integrable and Approximately Integrable Linear Statistical Models.- Nonparametric Techniques in Image Estimation.- Regularized Deconvolution on the Circle and the Sphere.- List of Attendants.- Contributed Papers.