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Activity Number:
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595
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 6, 2009 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #304896 |
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Title:
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A Two-Stage Hybrid Procedure for Estimating an Inverse Regression Function
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Author(s):
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Runlong Tang*+ and Moulinath Banerjee and George Michailidis
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Companies:
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University of Michigan and University of Michigan and University of Michigan
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Address:
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439 West Hall, 1085 South University, Ann Arbor, MI, 48109-1107,
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Keywords:
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inverse regression ; two stage ; isotonic regression ; bootstrap ;
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Abstract:
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We consider a two-stage procedure (TSP) for estimating an inverse egression function at a given point, where isotonic regression is used at Stage One to obtain an initial estimate and a local linear approximation in the vicinity of this estimate is used at Stage Two. We find that the convergence rate of the second-stage estimate can reach the parametric $n^{1/2}$ rate. Furthermore, a bootstrapped variant of TSP (BTSP) is provided to overcome the slow speed of the convergence in distribution and the estimation of a difficult unknown quantity. Finally, the finite sample performance of a practical variant of BTSP is studied through simulations.
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