Abstract Details
Activity Number:
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380
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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Abstract #311238
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View Presentation
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Title:
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Empirical Likelihood for Testing Function Constraints with Functional Data
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Author(s):
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Ping-Shou Zhong*+ and Honglang Wang and Yuehua Cui
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Companies:
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Michigan State University and Michigan State University and Michigan State University
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Keywords:
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Functional Constraint ;
Functional Data ;
Varying-Coefficient Model
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Abstract:
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Statistical inference for functional data has been receiving large attention due to the ever increasingly observed functional data in many scientific areas. In this work, we consider the problem of hypothesis testing for functions constraint in a varying-coefficient model framework for functional data. We propose an empirical likelihood-based approach to construct the test statistic. The asymptotic distribution of the test statistic is derived under the null hypothesis and local alternatives. It is shown that the proposed test is able to detect alternatives of root-n order for dense functional data. Both simulations and real data analysis are used to demonstrate our proposed method.
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Authors who are presenting talks have a * after their name.
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