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Activity Number:
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30
- Bayesian Modeling and Time Series
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Type:
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Contributed
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Date/Time:
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Sunday, July 30, 2017 : 2:00 PM to 3:50 PM
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Sponsor:
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Business and Economic Statistics Section
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Abstract #323617
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Title:
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Conditional Maximum Likelihood Estimation for a Class of Observation-Driven Time Series Models for Count Data
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Author(s):
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Yunwei Cui* and Qi Zheng
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Companies:
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Towson University and University of Louisville
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Keywords:
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observation-driven time series models ;
maximum likelihood estimation method ;
weak dependence
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Abstract:
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We investigate the statistical inference for a class of observation-driven time series models of count data based on the maximum likelihood estimation method, where the conditional distribution of the observed count given a state process is from the one-parameter exponential family. We also explore the weak dependence properties of the models. Under certain regularity conditions, the strong consistency and asymptotic normality of the estimators are established.
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Authors who are presenting talks have a * after their name.
