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Activity Number:
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203
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Type:
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Contributed
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Date/Time:
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Monday, August 7, 2006 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #305551 |
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Title:
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Median Regression Analysis from Doubly Censored Data
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Author(s):
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Sundar Subramanian*+
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Companies:
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University of Maine
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Address:
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5752 Neville Hall, Orono, ME, 04469-5752,
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Keywords:
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curse of dimensionality ; censoring distribution ; minimum dispersion statistic ; product integral ; Volterra integral equation
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Abstract:
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Median regression models provide a robust alternative to regression based on the mean. We propose a methodology for fitting a median regression model from data with both left- and right-censored observations in which the left-censoring variable is always observed. First, we set up an adjusted least-absolute-deviation-estimating function using the inverse-censoring weighted approach, whose solution specifies the estimator. We then describe the inference procedure for the regression parameter and determine the efficacy of the proposed procedure through simulation.
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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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