Standard Errors and Confidence Intervals in Inverse Problems: Sensitivity and Associated Pitfalls

Abstract

We review the asymptotic theory for standard errors in classical ordinary least squares (OLS) inverse or parameter estimation problems involving general nonlinear dynamical systems where sensitivity matrices can be used to compute the asymptotic covariance matrices. We discuss possible pitfalls in computing standard errors in regions of low parameter sensitivity and/or near a steady state solution of the underlying dynamical system.

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Document Details

Document Type
Technical Report
Publication Date
Mar 02, 2006
Accession Number
ADA444601

Entities

People

  • H. Thomas Banks
  • Sarah L. Grove
  • Stacey L. Ernstberger

Organizations

  • North Carolina State University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Computations
  • Covariance
  • Data Sets
  • Differential Equations
  • Engineering
  • Equations
  • Errors
  • Frequency
  • Intervals
  • Inverse Problems
  • Payload
  • Random Variables
  • Sampling
  • Sensitivity
  • Standards
  • Steady State

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Regression Analysis.