Partially Linear Models: A New Algorithm and some Simulation Results

Schimek, Michael G.

doi:10.1007/978-3-662-01131-7_62

Michael G. Schimek³

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Abstract

The problem of estimation in partially linear models is studied. We introduce an O(n) smoothing spline algorithm which extends the approaches of Speckuman (1988) and Green & Silverman (1994). It is known that the partial spline concept of Green & Silverman is asymptotically biased. In a Monte Carlo study we compare the small sample properties of the two approaches. The main outcome is that both concepts work well for uncorrelated predictor variables.

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References

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Authors and Affiliations

Department of Medical Informatics, Statistics and Documentation, Karl-Franzens-University of Graz, A-8010, Graz, Austria
Michael G. Schimek

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Michael G. Schimek
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Editors and Affiliations

Statistics Department, IACR-Rothamsted, AL5 2JQ, Harpenden, Herts, UK
Roger Payne
Department of Mathematics, University of Bristol, BS8 1TW, Bristol, UK
Peter Green

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Schimek, M.G. (1998). Partially Linear Models: A New Algorithm and some Simulation Results. In: Payne, R., Green, P. (eds) COMPSTAT. Physica, Heidelberg. https://doi.org/10.1007/978-3-662-01131-7_62

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DOI: https://doi.org/10.1007/978-3-662-01131-7_62
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1131-5
Online ISBN: 978-3-662-01131-7
eBook Packages: Springer Book Archive

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