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Activity Number: 30 - Bayesian Modeling and Time Series
Type: Contributed
Date/Time: Sunday, July 30, 2017 : 2:00 PM to 3:50 PM
Sponsor: Business and Economic Statistics Section
Abstract #323617
Title: Conditional Maximum Likelihood Estimation for a Class of Observation-Driven Time Series Models for Count Data
Author(s): Yunwei Cui* and Qi Zheng
Companies: Towson University and University of Louisville
Keywords: observation-driven time series models ; maximum likelihood estimation method ; weak dependence

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.

Authors who are presenting talks have a * after their name.

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