On Schur Optimality.

Abstract

Schur-optimality is defined (in the general setting of a linear model) as a generalization of the well-known D-, A- and E-optimality criteria. Techniques to establish Schur-optimality are outlined, based chiefly on a process of averaging information matrices and on vector majorization. A design with a completely symmetric information matrix of maximal trace and exactly two distinct nonzero eigenvalues is proved Schur-better than a large class of designs. One description of a subcollection of designs over which Schur-optimality holds is given only in terms of the diagonal elements of the information matrices. Consequences of this are then examined in the setting on block designs. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1980
Accession Number
ADA092185

Entities

People

  • Gregory M. Constantine

Organizations

  • Indiana University Bloomington

Tags

DTIC Thesaurus Topics

  • Air Force
  • Convex Sets
  • Data Science
  • Eigenvalues
  • Equations
  • Experimental Design
  • Identities
  • Information Science
  • Mathematics
  • New York
  • Permutations
  • Precision
  • Scientific Research
  • Spectra
  • Statistics
  • Theorems
  • Universities

Fields of Study

  • Mathematics

Readers

  • Linear Algebra
  • Regression Analysis.
  • Theoretical Analysis.