Non-Linear and Nonparametric Modelling of Seasonal Environmental Data

A. McMullan (), A. W. Bowman and E. M. Scott
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A. McMullan: University of Glasgow
A. W. Bowman: University of Glasgow
E. M. Scott: University of Glasgow

Computational Statistics, 2003, vol. 18, issue 2, No 1, 167-183

Abstract: Summary Non-linear models are often required in environmental applications, for example to incorporate seasonal effects. A wide variety of useful parametric forms is available, while nonparametric methods have the potential to offer further flexible extensions to any modelling situation. The aim of this paper is to incorporate this flexibility into non-linear models by allowing appropriate terms to vary smoothly over time. This uses the general structure of additive, semiparametric and varying coefficient models, within a non-linear setting. Data on water quality from the River Clyde are used as an example.

Keywords: additive models; semiparametric models; varying coefficient models; approximate F tests; pseudo-likelihood ratio test (search for similar items in EconPapers)
Date: 2003
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DOI: 10.1007/s001800300139

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