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Identify Design Conditions to Achieve the Optimal Rate of Convergence in a Bivariate Additive Model

2008 - 01 - 15 (Tue.)
13:30 - 15:00
405, Mathematics Research Center Building (ori. New Math. Bldg.)

This paper considers the estimation problem in a bivariate additive model, for . Here and is a random error and is assumed to be smooth which is approximated by B-splines. However, is not necessary to be smooth. This problem is motivated by the normalization needed in correcting intensity effects in microarray study. In this talk, an almost necessary and sufficient condition is given to guarantee that can be estimated with the usual one-dimensional optimal rate of convergence. We also present a simulation study to illustrate various convergence rate can be obtained when the proposed design condition is not satisfied.

Time:November 20, 2007 - July 31, 2009
Room:
Organizer:Hung Chen ( Department of Mathematics, National Taiwan University )

Available Talk List

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2008-01-08 (Tue.)		Nonparametric Estimation For Time-Dependent AUC
2008-01-15 (Tue.)		Identify Design Conditions to Achieve the Optimal Rate of Convergence in a Bivariate Additive Model
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2008-12-05 (Fri.)		General Adaptive Sparse Principal Component Analysis
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2008-12-26 (Fri.)		Review of paper “Semiparametric Estimation of Index Coefficients" by Powell J. L., Stock, J. H., and Stoker, T. M.
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2009-02-20 (Fri.)		Review of the paper ``Evaluating Prediction Rules for t-Year
2009-03-06 (Fri.)		Review on the Estimation of Prediction Error in terms of Covariance Penalty
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2009-04-10 (Fri.)		Review on the paper ``Partly conditional survival models for longitudinal data” (Zheng and Heagerty (2005)"
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