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The Basic Ideas of Obtaining MLEs: A Known Dispersion

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Part of the book series: Lecture Notes in Statistics ((LNS,volume 220))

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Abstract

Useful vector space decompositions are introduced. The classical Gauss-Markov model is used to illustrate the application of space decompositions. The approach is extended to cover tensor space decompositions which is a basic tool when considering bilinear regression models. The decompositions are illustrated in figures where one can follow how maximum likelihood estimators are obtained by projecting on appropriate subspaces.

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Authors and Affiliations

  1. Department of Energy and Technology, Swedish University of Agricultural Sciences, Uppsala, Sweden

    Dietrich von Rosen

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  1. Dietrich von Rosen
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von Rosen, D. (2018). The Basic Ideas of Obtaining MLEs: A Known Dispersion. In: Bilinear Regression Analysis. Lecture Notes in Statistics, vol 220. Springer, Cham. https://doi.org/10.1007/978-3-319-78784-8_2

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