THE MATRIX PSEUDOINVERSE AND MINIMAL VARIANCE ESTIMATES

Abstract

This paper reviews and applies certain results concerning the matrix pseudoinverse to the general theory of estimable functions and minimal variance estimates. The paper is divided into two sections. The first section reviews and extends certain known results concerning the matrix pseudoinverse. This section is essentially non statistical. The second section uses results in the first section to state and prove a generalized version of the Gauss-Markoff Theorem concerning unbiased linear estimates having minimal variance. In the third section, an additional theorem is proven, which together with the preceding material provides a theoretical foundation for parameter estimation in orbit determination work. This foundation is then exploited to provide formulae for such parameters.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1963
Accession Number
AD0405938

Entities

People

  • C. M. Price

Organizations

  • The Aerospace Corporation

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Air Force
  • Analysis Of Variance
  • California
  • Computer Programs
  • Eigenvalues
  • Eigenvectors
  • Identities
  • Materials
  • New York
  • Notation
  • Numbers
  • Procurement
  • Random Variables
  • Real Numbers
  • Space Systems
  • United States
  • Vector Spaces

Fields of Study

  • Mathematics

Readers

  • Business Analytics
  • Linear Algebra
  • Regression Analysis.

Technology Areas

  • Space