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Statistical Modelling
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Understanding past ocean circulations: a nonparametric regression case study

Richard Samworth

Statslab, Centre for Mathematical Sciences, Cambridge, UK, rjs57{at}cam.ac.uk

Heather Poore

Department of Earth Sciences, Bullard Laboratries, Madingley Road, Cambridge CB3 0EZ, UK

Oceanographers study past ocean circulations and their effect on global climate through carbon isotope records obtained from microfossils deposited on the ocean floor. An initial goal is to estimate the carbon isotope levels for the Pacific, Southern and North Atlantic Oceans over the last 23 million years and to provide confidence bands. We consider a nonparametric regression model and demonstrate how several recent developments in methodology make local linear kernel regression an attractive approach for tackling the problem. The results are used to estimate a quantity called the proportion of Northern Component Water and its effect on global climate. Several interesting and important geophysical and oceanographic conclusions are suggested by the study.

Key Words: confidence bands • errors-in-variables • local linear kernel estimator • model checking • non-parametric regression • Northern Component Water • SIMEX algorithm

Statistical Modelling, Vol. 5, No. 4, 289-307 (2005)
DOI: 10.1191/1471082X05st102oa


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