General Gauss–Markov Models

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


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.


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Authors and Affiliations

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

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