A comparison of mixed model splines for curve fitting

A - Papers appearing in refereed journals

Welham, S. J., Cullis, B. R., Kenward, M. G. and Thompson, R. 2007. A comparison of mixed model splines for curve fitting. Australian & New Zealand Journal of Statistics. 49 (1), pp. 1-23. https://doi.org/10.1111/j.1467-842X.2006.00454.x

AuthorsWelham, S. J., Cullis, B. R., Kenward, M. G. and Thompson, R.

Three types of polynomial mixed model splines have been proposed: smoothing splines, P-splines and penalized splines using a truncated power function basis. The close connections between these models are demonstrated, showing that the default cubic form of the splines differs only in the penalty used. A general definition of the mixed model spline is given that includes general constraints and can be used to produce natural or periodic splines. The impact of different penalties is demonstrated by evaluation across a set of functions with specific features, and shows that the best penalty in terms of mean squared error of prediction depends on both the form of the underlying function and the signal:noise ratio.

KeywordsStatistics & Probability
Year of Publication2007
JournalAustralian & New Zealand Journal of Statistics
Journal citation49 (1), pp. 1-23
Digital Object Identifier (DOI)https://doi.org/10.1111/j.1467-842X.2006.00454.x
Open accessPublished as non-open access
Funder project or codeCentre for Mathematical and Computational Biology (MCB)
Research in statistics relevant to biological processes
Output statusPublished
Publication dates
Online03 Feb 2007
Copyright licensePublisher copyright

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