Estimation of the Parameters of a Modified Compound Poisson Distribution.

Abstract

This paper addresses the problem of estimation of the parameters of the Poisson sum of Gaussian random variables imbedded in a background of Gaussian noise when only realizations of the sum are observable. Cumulant matching, maximum likelihood, and an empirically orthogonalized characteristic function procedures are considered. The characteristic function and the maximum likelihood procedures produce similar results in a simulation study. However, the characteristic function procedure is computationally superior. Conditions under which all procedures are incapable of parameter estimation are discussed. Keywords: random variables, normal distribution.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1986
Accession Number
ADA178540

Entities

People

  • A. S. Paulson
  • J. L. Bryant

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Covariance
  • Data Science
  • Distribution Functions
  • Equations
  • Estimators
  • Gaussian Distributions
  • Information Science
  • Maximum Likelihood Estimation
  • New York
  • Normal Distribution
  • Numerical Analysis
  • Random Variables
  • Simulations
  • Statistical Algorithms
  • Stochastic Processes
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Approximation Theory.
  • Mathematical Modeling and Probability Theory.