Informative Quantile Functions and Identification of Probability Distribution Types.

Abstract

A problem of great importance to statistical data analysts is quick identification of possible probability distributions for observed data, and classification of tail behavior of probability distributions. This paper discusses the informative quantile function IQ(u) = (Q(u) - Q(0.5)) divided by 2(Q(0.75) - Q(0.25)), and its use to identify probability models for observed data and its use to provide concepts of representative distributions which illustrate the different types of shapes and tail behavior that real distributions can have. This paper also discusses estimators of tail exponents; they can be used to identify outlying data values, and more centrally to identify possible distributions to fit to data. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1983
Accession Number
ADA132723

Entities

People

  • Emanuel Parzen

Organizations

  • Texas A&M University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Classification
  • Data Analysis
  • Data Mining
  • Data Science
  • Data Sets
  • Distribution Functions
  • Estimators
  • Gaussian Distributions
  • Information Science
  • Normal Distribution
  • Probability
  • Probability Distributions
  • Random Variables
  • Statistical Algorithms
  • Statistical Data
  • Statistics
  • Universities

Fields of Study

  • Mathematics

Readers

  • Statistical inference.
  • Systems Analysis and Design