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Activity Number:
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220
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Type:
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Contributed
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Date/Time:
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Monday, August 3, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #303303 |
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Title:
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A Theil-Type Estimate in Multiple Linear Regression and Its Asymptotics
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Author(s):
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Gang Shen*+
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Companies:
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Purdue University
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Address:
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Department of Statistics, 215 Nimitz Dr, West Lafayette, IN, 47906,
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Keywords:
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Theil's Estimate ; Oja median ; U-statistic ; Hoeffding's decomposition ; Convexity lemma
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Abstract:
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A Theil-type estimate for multiple linear regression models in the case of iid random covariates was proposed in Busarova et al (2006). It utilizes Oja spatial median on the elemental estimates of the regression coefficients. The essence of elemental estimate is that it transforms a regression problem into a location problem. This Theil-type estimate inherits affine-invariance and robustness in small sample. In this talk, I'll discuss this Theil-type estimate for the most interesting case, linear regression model with deterministic covariates, and its asymptotic distribution. The asymptotic relative efficiency (ARE) of this estimate in an example of orthogonal design will be also compared with that of LSE and LAD.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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