Abstract
To this point we have assumed that the relationship between the dependen variable Y and any independent variable X can be represented with a straight line. This clearly is inadequate in many cases. This chapter introduces the extensively used polynomial and trigonometric regression response models to characterize curvilinear relationships. Such models are linear in the parameters and linear least squares is appropriate for estimation of the parameters. Models that are nonlinear in the parameters are introduced in Chapter 15.
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© 1998 Springer-Verlag New York, Inc.
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(1998). Polynomial Regression. In: Rawlings, J.O., Pantula, S.G., Dickey, D.A. (eds) Applied Regression Analysis. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/0-387-22753-9_8
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DOI: https://doi.org/10.1007/0-387-22753-9_8
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-98454-4
Online ISBN: 978-0-387-22753-5
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