This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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56
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Type:
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Topic Contributed
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Date/Time:
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Sunday, August 1, 2010 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #306488 |
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Title:
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Multiscale Nonparametric Spectrum Estimation with Missing Observations
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Author(s):
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Thomas C.M. Lee*+ and Zhengyuan Zhu
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Companies:
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University of California, Davis and Iowa State University
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Address:
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, , CA, CA 95616,
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Keywords:
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multiscale methods ;
missing data ;
spectral density ;
wavelets
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Abstract:
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Self-consistency is a fundamental principle in statistics for retaining maximum amount of information in the data. In this paper this principle is applied to develop a new method for nonparametric spectrum estimation with missing data. One major advantage of the proposed method is that it can be coupled with any complete data nonparametric spectrum estimation procedure, including multiscale wavelet estimators. The practical performance of the method is illustrated by a simulation study.
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