An alternative look at the linear regression model

Autor: Oskar Maria Baksalary, Götz Trenkler
Rok vydání: 2022
Předmět:
Zdroj: Statistical Papers. 63:1499-1509
ISSN: 1613-9798
0932-5026
Popis: An alternative look at the linear regression model is taken by proposing an original treatment of a full column rank model (design) matrix. In such a situation, the Moore–Penrose inverse of the matrix can be obtained by utilizing a particular formula which is applicable solely when a matrix to be inverted can be columnwise partitioned into two matrices of disjoint ranges. It turns out that this approach, besides simplifying derivations, provides a novel insight into some of the notions involved in the model and reduces computational costs needed to obtain sought estimators. The paper contains also a numerical example based on astronomical observations of the localization of Polaris, demonstrating usefulness of the proposed approach.
Databáze: OpenAIRE
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