This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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249
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Type:
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Contributed
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Date/Time:
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Monday, August 2, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics and the Environment
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Abstract - #306694 |
Title:
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Some Asymptotics for Geostatistical Model Selection
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Author(s):
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Hsin-Cheng Huang*+
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Companies:
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Academia Sinica
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Address:
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128-22 Sec.2 Academia Rd., Taipei, International, 115, Taiwan
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Keywords:
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Akaike information criterion ;
Bayesian information criterion ;
conditional information criterion ;
fixed domain asymptotic ;
increasing domain asymptotic ;
variable selection
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Abstract:
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Information criteria such as AIC and BIC are often used in model selection. However, their asymptotic behaviors in geostatistical model selection have not been well studied, particularly under fixed domain asymptotics based on increasing dense data observed in a fixed and bounded region. In fact, some spatial dependent parameters can't be consistently estimated by maximum likelihood under fixed domain asymptotics, thus making the problem difficult to handle. In this talk, I will first show some asymptotic properties of the generalized information criterion, including AIC and BIC. In addition, I will introduce a class of conditional information criteria extended from the conditional AIC, and provide some numerical and theoretical justification.
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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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