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General Gauss–Markov Models

Chapter
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Part of the Springer Texts in Statistics book series (STS)

Abstract

The standard linear model assumes the data vector has a covariance matrix of \(\sigma ^2 I\). Sections 2.7 and 3.8 extended the theory to having a covariance matrix of \(\sigma ^2 V\) where V was known and positive definite. This chapter extends the theory by allowing V to be merely nonnegative definite.

References

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Mathematics and StatisticsUniversity of New MexicoAlbuquerqueUSA

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