Abstract
Chapter 14 completed the series of chapters devoted to problem areas in least squares regression. This chapter returns to regression methods for fitting a variety of models. Chapter 8 introduced the use of polynomial and trigonometric response models for characterizing responses that cannot be adequately represented by straight-line relationships. This chapter extends those ideas to the large class of usually more realistic models that are nonlinear in the parameters. First, several examples of nonlinear models are given. Then regression methods for fitting these models are presented.
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© 1998 Springer-Verlag New York, Inc.
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(1998). Models Nonlinear in the Parameters. 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_15
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DOI: https://doi.org/10.1007/0-387-22753-9_15
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-98454-4
Online ISBN: 978-0-387-22753-5
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