Mathematical and Statistical Characterizations of Generalized Hyperexponential Distribution Functions.

Abstract

This paper examines in detail the class of generalized hyperexponential (GH) probability distribution functions. The family is compared to and contrasted with similar popular classes of distributions used in stochastic modeling. Each of these families arises from a desire to preserve the computationally attractive feature of memorylessness possessed by the exponential probability distribution while extending the representations to a broader class in order to approximate an arbitrary probability distribution function. Thus, the simple structure and attractive properties of the GH probability distribution functions are presented with a view toward facilitating the mathematical operations which frequently occur in practice. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1986
Accession Number
ADA165892

Entities

People

  • Carl M. Harris
  • Robert F. Botta
  • William G. Marchal

Organizations

  • George Mason University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Differential Equations
  • Distribution Functions
  • Engineering
  • Equations
  • Markov Chains
  • Mathematics
  • Maximum Likelihood Estimation
  • New York
  • Numerical Analysis
  • Order Statistics
  • Probability
  • Probability Distribution Functions
  • Probability Distributions
  • Random Variables
  • Statistics
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Mathematical Modeling and Probability Theory.
  • Military History / Militaries and War Studies