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Activity Number:
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18
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Type:
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Topic Contributed
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Date/Time:
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Sunday, July 29, 2007 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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| Abstract - #308853 |
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Title:
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Block Bootstrap Procedures for Modeling Inhomogeneous Spatial Point Patterns
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Author(s):
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Yongtao Guan*+
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Companies:
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Yale University
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Address:
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60 College Street, New Haven, CT, 06520-8034,
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Keywords:
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Block Bootstrap ; Inhomogeneous Spatial Point Process
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Abstract:
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When modeling inhomogeneous spatial point patterns, it is often of interest to fit a parametric model for the first order intensity function (FOIF) of the process in terms of some measured environmental covariates. Estimates for the unknown coefficients can be obtained by maximizing a Poisson maximum likelihood criterion. We propose new block bootstrap procedures to estimate the variance of the estimated parameters. These procedures depend only on the FOIF of the process but not on any high-order terms and thus can be easily applied once the FOIF has been estimated. We demonstrate the use of these procedures through both simulations and an application to a tropical forestry data example.
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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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