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A Maximal Extension of the Gauss–Markov Theorem and Its Nonlinear Version

✍ Scribed by Takeaki Kariya; Hiroshi Kurata


Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
149 KB
Volume
83
Category
Article
ISSN
0047-259X

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✦ Synopsis


In this paper, first we make a maximal extension of the well-known Gauss-Markov Theorem (GMT) in its linear framework. In particular, the maximal class of distributions of error term for which the GMT holds is derived. Second, we establish a nonlinear version of the maximal GMT and describe some interesting families of distributions of error term for which the nonlinear GMT holds.