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Things are not Always Linear; Additive Modelling

  • Alain F. Zuur
  • Elena N. Ieno
  • Neil J. Walker
  • Anatoly A. Saveliev
  • Graham M. Smith
Chapter
Part of the Statistics for Biology and Health book series (SBH)

Abstract

In the previous chapter, we looked at linear regression, and although the word linear implies modelling only linear relationships, this is not necessarily the case. A model of the form Y i = α + β 1 × X i + β 2 × X i 2 + ɛ i is a linear regression model, but the relationship between Y i and X i is modelled using a second-order polynomial function. The same holds if an interaction term is used. For example, in Chapter 2, we modelled the biomass of wedge clams as a function of length, month and the interaction between length and month. But a scatterplot between biomass and length may not necessarily show a linear pattern.

Keywords

Akaike Information Criterion Linear Regression Model Generalise Additive Model Regression Spline Smoothing Spline 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Alain F. Zuur
    • 1
  • Elena N. Ieno
    • 1
  • Neil J. Walker
    • 2
  • Anatoly A. Saveliev
    • 3
  • Graham M. Smith
    • 4
  1. 1.Highland Statistics LtdNewburghUK
  2. 2.Central Science LaboratoryGloucesterUK
  3. 3.Kazan State UniversityKazanRussia
  4. 4.Bath Spa UniversityBathUK

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