Smooth Nonparametric Regression Analysis.

Abstract

This work investigates properties of the Watson type estimator of the regression function EY bar X = x of a bivariate random vector (X,Y). Pointwise weak consistency of the estimator is demonstrated. Sufficient conditions are given for asymptotic joint normality of the estimator taken at a finite number of distinct points, and for the uniform consistency of the estimator over a bounded interval. A large sample confidence band for the regression function, based on the estimator, is derived. (Author)

Keywords

*NONPARAMETRIC STATISTICS
ESTIMATES
KERNEL FUNCTIONS
REGRESSION ANALYSIS
BIVARIATE ANALYSIS
CONFIDENCE LEVEL
ASYMPTOTIC NORMALITY
GAUSSIAN QUADRATURE

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