Role of Auxiliary Variate and Additional Data in Density Estimation.

Abstract

Some new estimators of a univariate probability density function f(y) of a random variable Y, based on a set of observations taken from a bivariate joint density beta(x,y) of Y and a suitably chosen concomitant variable X, have been investigated. Asymptotic unbiasedness, mean square consistency, asymptotic normality and rates of convergence have been established. A related problem of estimation of a conditional density has also been studied. Keywords: Kernel Method; Unbiasedness; Mean Square Consistencies; Rate of Convergence.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1985
Accession Number
ADA160287

Entities

People

  • Masab Ahmad
  • R. S. Singh

Organizations

  • University of Pittsburgh

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Air Force
  • Asymptotic Normality
  • Data Science
  • Data Sets
  • Estimators
  • Heuristic Methods
  • Information Science
  • Monte Carlo Method
  • Multivariate Analysis
  • Normality
  • Observation
  • Probability
  • Probability Density Functions
  • Random Variables
  • Statistical Algorithms
  • Theorems
  • United States Government

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Regression Analysis.