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Estimation and Testing in General Gauss-Markov Models

  • Ronald Christensen
Part of the Springer Texts in Statistics book series (STS)

Abstract

A general Gauss-Markov model is a model
$$Y = X\beta + e,E(e) = 0,Cov(e) = {\sigma ^2}V$$
, where V is a known matrix. Linear models can be divided into four categories depending on the assumptions made about V:
  1. (a)

    V is an identity matrix,

     
  2. (b)

    V is nonsingular,

     
  3. (c)

    V is possibly singular but C(X)⊂ C(V),

     
  4. (d)

    V is possibly singular.

     

Keywords

Unbiased Estimate Consistent Estimate Geometric Aspect Linear Unbiased Estimate Well Linear Unbiased Estimate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • Ronald Christensen
    • 1
  1. 1.Department of Mathematics and StatisticsUniversity of New MexicoAlbuquerqueUSA

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