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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101
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Type:
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Invited
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Date/Time:
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Monday, August 2, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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SSC
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| Abstract - #305934 |
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Title:
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A General Numerical Method for Probability Mass Functions in Count Data Time Series
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Author(s):
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Rong Zhu*+ and Harry Joe
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Companies:
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McMaster University and The University of British Columbia
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Address:
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Department of Mathematics and Statistics, Hamilton, ON, L8S 4K1, Canada
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Keywords:
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negative binomial time series ;
binomial thinning ;
expectation thinning ;
generalized discrete self-decomposability ;
compounding operation ;
inversion of characteristic function
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Abstract:
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Count data time series models based on expectation thinning operators do not have explicit forms of conditional and innovation probability mass functions (pmf's) except for a few cases related to the Poisson margin. In order to do simulations, likelihood inference, graphical diagnostics and prediction, we adopt a numerical method to compute relevant pmf's by the inversion of characteristic functions. We illustrate the numerical methods and compare the various negative binomial time series models for a real data example.
This is a joint work with Professor Harry Joe in the Department of Statistics at UBC.
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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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