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Data-driven selection of the spline dimension in penalized spline regression

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  • Göran Kauermann
  • Jean D. Opsomer

Abstract

A number of criteria exist to select the penalty in penalized spline regression, but the selection of the number of spline basis functions has received much less attention in the literature. We propose a likelihood-based criterion to select the number of basis functions in penalized spline regression. The criterion is easy to apply and we describe its theoretical and practical properties. Copyright 2011, Oxford University Press.

Suggested Citation

  • Göran Kauermann & Jean D. Opsomer, 2011. "Data-driven selection of the spline dimension in penalized spline regression," Biometrika, Biometrika Trust, vol. 98(1), pages 225-230.
    • Handle: RePEc:oup:biomet:v:98:y:2011:i:1:p:225-230
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    File URL: http://hdl.handle.net/10.1093/biomet/asq081
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    Citations

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    Cited by:

    1. Christian Schellhase & Göran Kauermann, 2012. "Density estimation and comparison with a penalized mixture approach," Computational Statistics, Springer, vol. 27(4), pages 757-777, December.
    2. Kuhlenkasper, Torben & Steinhardt, Max Friedrich, 2017. "Who leaves and when? Selective outmigration of immigrants from Germany," Economic Systems, Elsevier, vol. 41(4), pages 610-621.
    3. Nina Westerheide & Goran Kauermann, 2014. "Unemployed in Germany: Factors Influencing the Risk of Losing the Job," Research in World Economy, Research in World Economy, Sciedu Press, vol. 5(2), pages 43-55, September.
    4. Michael Wegener & Göran Kauermann, 2017. "Forecasting in nonlinear univariate time series using penalized splines," Statistical Papers, Springer, vol. 58(3), pages 557-576, September.
    5. Rose Baker & Dan Jackson, 2014. "Statistical application of barycentric rational interpolants: an alternative to splines," Computational Statistics, Springer, vol. 29(5), pages 1065-1081, October.
    6. Patricio Maturana-Russel & Renate Meyer, 2021. "Bayesian spectral density estimation using P-splines with quantile-based knot placement," Computational Statistics, Springer, vol. 36(3), pages 2055-2077, September.
    7. Blöchl, Andreas, 2014. "Trend Estimation with Penalized Splines as Mixed Models for Series with Structural Breaks," Discussion Papers in Economics 18446, University of Munich, Department of Economics.
    8. Bloechl, Andreas, 2014. "Penalized Splines, Mixed Models and the Wiener-Kolmogorov Filter," Discussion Papers in Economics 21406, University of Munich, Department of Economics.
    9. Smith, Michael S. & Kauermann, Göran, 2011. "Bicycle commuting in Melbourne during the 2000s energy crisis: A semiparametric analysis of intraday volumes," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1846-1862.
    10. Torben Kuhlenkasper & Max Friedrich Steinhardt, 2011. "Unemployment Duration in Germany – A comprehensive study with dynamic hazard models and P-Splines," Norface Discussion Paper Series 2011018, Norface Research Programme on Migration, Department of Economics, University College London.

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