Abstract
The main topic of this chapter is the linear regression model with more than one independent variables. The principles of least squares and maximum likelihood are used for the estimation of parameters. We present the algebraic, geometric, and statistical aspects of the problem, each of which has an intuitive appeal.
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© 2008 Springer-Verlag Berlin Heidelberg
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(2008). The Multiple Linear Regression Model and Its Extensions. In: Linear Models and Generalizations. Springer Series in Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74227-2_3
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DOI: https://doi.org/10.1007/978-3-540-74227-2_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74226-5
Online ISBN: 978-3-540-74227-2
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)