Building an MLR Model

David J. Olive
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David J. Olive: Southern Illinois University, Department of Mathematics

Chapter Chapter 3 in Linear Regression, 2017, pp 85-162 from Springer

Abstract: Abstract Building a multiple linear regression (MLR) model from data is one of the most challenging regression problems. The “final full model” will have response variable Y = t(Z), a constant x 1, and predictor variables x 2 = t 2(w 2, …, w r ), …, x p = t p (w 2, …, w r ) where the initial data consists of Z, w 2, …, w r . Choosing t, t 2, …, t p so that the final full model is a useful MLR approximation to the data can be difficult.

Date: 2017
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DOI: 10.1007/978-3-319-55252-1_3

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