A Comparison of Approximation Methods for the Estimation of Probability Distributions on Parameters

Abstract

In this paper, we compare two computationally efficient approximation methods for the estimation of growth rate distributions in size-structured population models. After summarizing the underlying theoretical framework, we present several numerical examples as validation of the theory. Furthermore, we compare the results from a spline based approximation method and a delta function based approximation method for the inverse problem involving the estimation of the distributions of growth rates in size-structured mosquitofish populations. Convergence as well as sensitivity of the estimates with respect to noise in the data are discussed for both approximation methods.

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Document Details

Document Type
Technical Report
Publication Date
Oct 10, 2005
Accession Number
ADA440143

Entities

People

  • H. Thomas Banks
  • N. L. Gibson

Organizations

  • North Carolina State University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Computational Science
  • Computer Programming
  • Covariance
  • Data Sets
  • Delta Functions
  • Estimators
  • Fish
  • Gaussian Distributions
  • Inverse Problems
  • Mathematical Models
  • Models
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Quadratic Programming
  • Random Variables
  • Statistical Analysis

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Regression Analysis.