LINEAR LEAST SQUARES REGRESSION.

Abstract

The paper gives a self contained account of linear least squares regression when the errors have an arbitrary error covariance matrix. The finite sample size case is treated algebraically by methods which are entirely analogous to those used for the asymptotic study of the same problem by spectral analysis when the errors are generated by a covariance stationary process. The algebraic methods and results are of interest in themselves and may also be useful as an introduction to the difficult analysis involved in the asymptotic treatment. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1966
Accession Number
AD0637245

Entities

People

  • Geoffrey S. Watson

Organizations

  • Johns Hopkins University

Tags

DTIC Thesaurus Topics

  • Computing-Related Activities
  • Covariance
  • Data Science
  • Information Science
  • Interdisciplinary Science
  • Mathematical Analysis
  • Mathematics
  • Stationary
  • Stationary Processes
  • Statistical Analysis

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Calculus or Mathematical Analysis