ABSTRACT

Model a Wide Range of Count Time Series Handbook of Discrete-Valued Time Series presents state-of-the-art methods for modeling time series of counts and incorporates frequentist and Bayesian approaches for discrete-valued spatio-temporal data and multivariate data. While the book focuses on time series of counts, some of the techniques discussed ca

section Section I|186 pages

Methods for Univariate Count Processes

chapter 1|25 pages

Statistical Analysis of Count Time Series Models: A GLM Perspective

ByKonstantinos Fokianos

chapter 2|21 pages

Markov Models for Count Time Series

ByHarry Joe

chapter 3|26 pages

Generalized Linear Autoregressive Moving Average Models

ByWilliam T.M. Dunsmuir

chapter 5|20 pages

Renewal-Based Count Time Series

ByRobert Lund, James Livsey

chapter 6|24 pages

State Space Models for Count Time Series

ByRichard A. Davis, William T.M. Dunsmuir

chapter 7|19 pages

Estimating Equation Approaches for Integer-Valued Time Series Models

ByAerambamoorthy Thavaneswaran, Nalini Ravishanker

chapter 8|22 pages

Dynamic Bayesian Models for Discrete-Valued Time Series

ByDani Gamerman, Carlos A. Abanto-Valle, Ralph S. Silva, Thiago G. Martins

section Section II|78 pages

Diagnostics and Applications

chapter 9|30 pages

Model Validation and Diagnostics

ByRobert C. Jung, Brendan P.M. McCabe, A.R. Tremayne

chapter 10|26 pages

Detection of Change Points in Discrete-Valued Time Series

ByClaudia Kirch, Joseph Tadjuidje Kamgaing

chapter 11|20 pages

Bayesian Modeling of Time Series of Counts with Business Applications

ByRefik Soyer, Tevfik Aktekin, Bumsoo Kim

section Section III|59 pages

Binary and Categorical-Valued Time Series

chapter 12|20 pages

Hidden Markov Models for Discrete-Valued Time Series

ByIain L. MacDonald, Walter Zucchini

chapter 13|24 pages

Spectral Analysis of Qualitative Time Series

ByDavid Stoffer

chapter 14|13 pages

Coherence Consideration in Binary Time Series Analysis

ByBenjamin Kedem

section Section IV|80 pages

Discrete-Valued Spatio-Temporal Processes

chapter 15|21 pages

Hierarchical Dynamic Generalized Linear Mixed Models for Discrete-Valued Spatio-Temporal Data

ByScott H. Holan, Christopher K. Wikle

chapter 16|17 pages

Hierarchical Agent-Based Spatio-Temporal Dynamic Models for Discrete-Valued Data

ByChristopher K. Wikle, Mevin B. Hooten

chapter 17|19 pages

Autologistic Regression Models for Spatio-Temporal Binary Data

ByJun Zhu, Yanbing Zheng

chapter 18|18 pages

Spatio-Temporal Modeling for Small Area Health Analysis

ByAndrew B. Lawson, Ana Corberán-Vallet

section Section V|54 pages

Multivariate and Long Memory Discrete-Valued Processes

chapter 19|18 pages

Models for Multivariate Count Time Series

ByDimitris Karlis

chapter 20|21 pages

Dynamic Models for Time Series of Counts with a Marketing Application

ByNalini Ravishanker, Rajkumar Venkatesan, Shan Hu

chapter 21|12 pages

Long Memory Discrete-Valued Time Series

ByRobert Lund, Scott H. Holan, James Livsey