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Activity Number: 99
Type: Invited
Date/Time: Monday, August 1, 2016 : 8:30 AM to 10:20 AM
Sponsor: Business and Economic Statistics Section
Abstract #318280
Title: Modeling and Inference for Multivariate Count Time Series
Author(s): Konstantinos Fokianos* and Paul Doukhan and Bard Stove and Dag Tjostheim
Companies: University of Cyprus and University Cergy-Pontoise and University of Bergen and University of Bergen
Keywords: autocorrelation ; copula ; distance covariance matrix ; ergodicity ; generalized linear models ; prediction

We are studying the problems of modeling and inference for multivariate count time series data. We provide a conceptual framework for studying the theoretical of such processes. We suggest suitable estimating equations for implementing inference and we study the large sample properties of the resulting estimators. The model fitting process is examined by a test of pairwise independence which is formed by means of the distance covariance matrix. Our presentation is coupled with real data examples.

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

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