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Abstract Details
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Activity Number:
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576
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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| Abstract - #306666 |
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Title:
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Empirical Likelihood Inference for Parameters of Spatial Branching Process
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Author(s):
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Pin Ren*+ and Anand N. Vidyashankar
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Companies:
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and George Mason University
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Address:
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13155 Quail Creek Lane, Fairfax, VA, 22033-5407, United States
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Keywords:
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spatial branching process ;
large deviations ;
empirical ;
dual likelihood ;
Wilk's phenomenon
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Abstract:
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Spatial branching processes arise in multiple areas of scientific applications such as epidemic spread, page ranking algorithms, cell biology, and finance. Inference concerning parameters describing these processes is challenging due to the natural constraints satisfied by them. Furthermore, these parameters characterize certain rare events which have important scientific interpretations. In this talk, we will describe how empirical likelihood based estimation and inferential methods can be developed for these problems using a specific large deviation change of measure idea. We will describe the asymptotic properties of the proposed maximum empirical likelihood estimator and of the appropriately scaled empirical likelihood ratio statistic. A novel computational method and simulations in small samples will also be described.
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Authors who are presenting talks have a * after their name.
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