An Intuitive Geometric Approach to the Gauss Markov Theorem

作者:Pereira Leandro da Silva*; Chaves Lucas Monteiro; de Souza Devanil Jaques
来源:American Statistician, 2017, 71(1): 67-70.
DOI:10.1080/00031305.2016.1209127

摘要

Algebraic proofs of Gauss-Markov theorem are very disappointing from an intuitive point of view. An alternative is to use geometry that emphasizes the essential statistical ideas behind the result. This article presents a truly geometrical intuitive approach to the theorem, based only in simple geometrical concepts, like linear subspaces and orthogonal projections.

  • 出版日期2017