| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1152388 | Statistics & Probability Letters | 2012 | 7 Pages |
Abstract
We consider generalized linear models for regression modeling of count time series. We give easily verifiable conditions for obtaining weak dependence for such models. These results enable the development of maximum likelihood inference under minimal conditions. Some examples which are useful to applications are discussed in detail.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Paul Doukhan, Konstantinos Fokianos, Dag Tjøstheim,