Empirical Quantile Function Nonparametric Integrated Analyses

Abstract

This three-year statistics research project addressed theoretical development, efficiency evaluation, and desktop computer implementation of an integrated nonparametric statistical data analysis approach based on Fourier analytic techniques applied to the empirical quantile function (EQF). New EQF statistical procedures were developed for data smoothing and reduction methods, nonparametric estimation of various functionals associated with the quantile function, composite goodness-of-fit tests for uniform and exponential models with applications to related stochastic processes, and nonparametric analysis of variance rank procedures for analysis of independent samples. These EQF methods exploit discrete Hahn polynomial orthogonal polynomial component representations to produce statistics for significance testing and interval estimation for both omnibus and directional alternative models. Performance evaluations of the proposed techniques included theoretical and Monte Carlo efficiency comparisons as well as numerical applications to challenging data sets. Interactive desktop computer and graphics routines utilizing symbolic programming languages were developed to facilitate implementation of EQF data analysis techniques by statistical users. Nonparametric Statistics, Quantile Function, Goodness of Fit, Components.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1993
Accession Number
ADA263704

Entities

People

  • W. D. Kaigh

Organizations

  • University of Texas at El Paso

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Computational Science
  • Computer Programming
  • Computers
  • Data Analysis
  • Data Mining
  • Data Science
  • Goodness Of Fit Tests
  • Information Processing
  • Information Science
  • Knowledge Management
  • Order Statistics
  • Programming Languages
  • Statistical Analysis
  • Statistical Data
  • Statistics
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Computer Science.
  • Statistical inference.