ON THE EXTENSION OF GAUSS-MARKOV THEOREM TO SUBSETS OF THE PARAMETER SPACE UNDER COMPLEX MULTIVARIATE LINEAR MODELS,

Abstract

The paper concerns the problem of linear estimation (without the assumption of normality) under certain general kinds of multiresponse linear models. These include the general incomplete multiresponse (GIM) model and its important special case, the hierarchical multiresponse (HM) model, and also the multiple design multiresponse (MDM) model. These were considered in Srivastava (1967), where the general problem of obtaining the best linear unbiased estimate (BLUE) of general linear functions of the location parameters was investigated. The study is continued here in the direction of obtaining necessary and sufficient conditions for each of the above models to permit the existence of BLU estimates for all elements in a subset of the set of all estimate linear functions of the location parameters. (Author)

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1970
Accession Number
AD0708165

Entities

People

  • J. N. Srivastava
  • Lyman Mcdonald

Organizations

  • Colorado State University

Tags

DTIC Thesaurus Topics

  • Computing-Related Activities
  • Data Science
  • Information Science
  • Interdisciplinary Science
  • Mathematical Analysis
  • Mathematics
  • Normality

Fields of Study

  • Mathematics

Readers

  • Battery Technology and Engineering
  • Operations Research
  • Statistical inference.

Technology Areas

  • Space