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Activity Number:
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540
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Type:
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Contributed
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Date/Time:
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Thursday, August 2, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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ENAR
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| Abstract - #310366 |
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Title:
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Efficient Estimation of Population Quantiles in General Semiparametric Regression Models
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Author(s):
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Arnab Maity*+
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Companies:
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Texas A&M University
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Address:
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Department of Statistics, College Station, TX, 77843,
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Keywords:
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Abstract:
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This paper considers a large family of semiparametric regression models, in which the main interest is on estimating population quantiles. Special cases of our framework include generalized partially linear models, generalized partially linear single index models, structural measurement error models and many others. We derive plug-in kernel-based estimators of the population quantiles of random variables and derive their asymptotic distribution. We also establish the semiparametric efficiency of these estimators under mild assumptions. We apply our methodology in an example in nutritional epidemiology where estimation of quantiles of usual intake of various dietary components are of primary interest. The generalization to the important case that responses are missing at random is also addressed.
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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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