Handbook of Discrete-Valued Time Series

Section I: Methods for Univariate Count Processes
1. Statistical Analysis of Count Time Series Models: A GLM Perspective by Konstantinos Fokianos
2. Markov Models for Count Time Series by Harry Joe
3. Generalized Linear Autoregressive Moving Average Models by William T. M. Dunsmuir
4. Count Time Series with Observation-Driven Autoregressive Parameter Dynamics by Dag Tjøstheim
5. Renewal-Based Count Time Series by James Livsey
6. State Space Models for Count Time Series by William T. M. Dunsmuir
7. Estimating Equation Approaches for Integer-Valued Time Series Models by Nalini Ravishanker
8. Dynamic Bayesian Models for Discrete-Valued Time Series by Thiago G. Martins

Section II: Diagnostics and Applications
9. Model Validation and Diagnostics by A. R. Tremayne
10. Detection of Change Points in Discrete-Valued Time Series by Joseph Tadjuidje Kamgaing
11. Bayesian Modeling of Time Series of Counts with Business Applications by Bumsoo Kim

Section III: Binary and Categorical-Valued Time Series
12. Hidden Markov Models for Discrete-Valued Time Series by Walter Zucchini
13. Spectral Analysis of Qualitative Time Series by David Stoffer
14. Coherence Consideration in Binary Time Series Analysis by Benjamin Kedem

Section IV: Discrete-Valued Spatio-Temporal Processes
15. Hierarchical Dynamic Generalized Linear Mixed Models for Discrete-Valued Spatio-Temporal Data by Christopher K. Wikle
16. Hierarchical Agent-Based Spatio-Temporal Dynamic Models for Discrete-Valued Data by Mevin B. Hooten
17. Autologistic Regression Models for Spatio-Temporal Binary Data by Yanbing Zheng
18. Spatio-Temporal Modeling for Small Area Health Analysis by Ana Corberan-Vallet

Section V: Multivariate and Long Memory Discrete-Valued Processes
19. Models for Multivariate Count Time Series by Dimitris Karlis
20. Dynamic Models for Time Series of Counts with a Marketing Application by Shan Hu
21.Long Memory Discrete-Valued Time Series by James Livsey