Nonparametric Sequential Estimation of Zeros and Extrema of Regression Functions.

Abstract

Let (X,Y), (X sub 1, Y sub 1), (X sub 2, Y sub 2, ... be independent, identically distributed, bivariate random variables and let m(x)=E(Y/X=x) be the regression curve of y on X. This paper considers the estimation of zeros and extrema of the regression curve via stochastic approximation methods. The author presents consistency results of some sequential procedures and define termination rules providing fixed width confidence intervals for the parameters to be estimated. Keywords: kernel regression; nonparametric regression. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1986
Accession Number
ADA169958

Entities

People

  • Wolfgang Haerdle

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Asymptotic Normality
  • Data Science
  • Estimators
  • Forensic Medicine
  • Gaussian Processes
  • Information Science
  • Intervals
  • Normal Distribution
  • Normality
  • North Carolina
  • Probability
  • Random Variables
  • Sequences
  • Statistics
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Statistical inference.