Conditional Heteroskedasticity in Count Data Regression: Self-Feeding Activity in Fish
- 1 January 2004
- journal article
- Published by Taylor & Francis in Communications in Statistics - Theory and Methods
- Vol. 33 (11) , 2745-2758
- https://doi.org/10.1081/sta-200037877
Abstract
This paper introduces a new approach to incorporating time-dependent overdispersion for Poisson-related regression models. To handle the added flexibility in conditional heteroskedasticity in time series count data models, some well-known estimators are adapted, and a generalized method of moments (GMM) estimator is suggested. The estimators are applied to a time series of self-feeding activity in Arctic charr. There is strong support for both a dynamic conditional mean function and a dynamic model for the overdispersion.Keywords
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