Non-parametric Quantile Estimation Through Stochastic Approximation.

Abstract

The extreme values which a random variable X may take on are usually best characterized by the quantiles of the random variable. Known non-parametric methods for the statistical estimation of extreme quantiles all suffer from serious shortcomings, however. In this thesis a robust and efficient method for quantile estimation is described; both the asymptotic and finite sample properties of the estimator are determined and computer implementations are given. Possible applications for the technique include the analysis of computer simulations and data analysis in large data bases or real time computer systems.

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1975
Accession Number
ADA014628

Entities

People

  • David Walter Robinson

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Computer Simulations
  • Computers
  • Computing-Related Activities
  • Data Analysis
  • Data Science
  • Databases
  • Estimators
  • Information Science
  • Mathematics
  • Random Variables
  • Simulations
  • Simulators
  • Statistical Estimation

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.