Handbook of Discrete-Valued Time Series / editors, Scott H. Holan, Robert Lund.

Format:

Book

Author/Creator:

Davis, Richard A., author.

Contributor:

Holan, Scott H., editor.

Lund, Robert, editor.

Ravishanker, Nalini, editor.

Series:

Chapman & Hall/CRC handbooks of modern statistical methods.

Chapman & Hall/CRC Handbooks of Modern Statistical Methods

Language:

English

Subjects (All):

Time-series analysis.

Discrete-time systems--Mathematical models.

Discrete-time systems.

Linear systems--Mathematical models.

Linear systems.

Physical Description:

1 online resource (480 pages) : illustrations.

Edition:

First edition.

Place of Publication:

Boca Raton, FL : CRC Press, 2016.

Summary:

"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 can be applied to other types of discrete-valued time series, such as binary-valued or categorical time series.Explore a Balanced Treatment of Frequentist and Bayesian Perspectives Accessible to graduate-level students who have taken an elementary class in statistical time series analysis, the book begins with the history and current methods for modeling and analyzing univariate count series. It next discusses diagnostics and applications before proceeding to binary and categorical time series. The book then provides a guide to modern methods for discrete-valued spatio-temporal data, illustrating how far modern applications have evolved from their roots. The book ends with a focus on multivariate and long-memory count series.Get Guidance from Masters in the FieldWritten by a cohesive group of distinguished contributors, this handbook provides a unified account of the diverse techniques available for observation- and parameter-driven models. It covers likelihood and approximate likelihood methods, estimating equations, simulation methods, and a Bayesian approach for model fitting."--Provided by publisher.

Contents:

Methods for Univariate Count Processes

Statistical Analysis of Count Time Series Models: AGLM Perspective

Konstantinos Fokianos

Markov Models for Count Time Series

Harry Joe

Generalized Linear Autoregressive Moving Average Models

William T.M. Dunsmuir

Count Time Series with Observation-Driven Autoregressive Parameter Dynamics

Dag Tjøstheim

Renewal-Based Count Time Series

Robert Lund and James Livsey

State Space Models for Count Time Series

Richard A. Davis and William T.M. Dunsmuir

Estimating Equation Approaches for Integer-Valued Time Series Models

Aerambamoorthy Thavaneswaran and Nalini Ravishanker

Dynamic Bayesian Models for Discrete-Valued Time Series

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

Diagnostics and Applications

Model Validation and Diagnostics

Robert C. Jung, Brendan P.M. McCabe, and A.R. Tremayne

Detection of Change Points in Discrete-Valued Time Series

Claudia Kirch and Joseph Tadjuidje Kamgaing

Bayesian Modeling of Time Series of Counts with Business Applications

Refik Soyer, Tevfik Aktekin, and Bumsoo Kim

Binary and Categorical-Valued Time Series

Hidden Markov Models for Discrete-Valued Time Series

Iain L. MacDonald and Walter Zucchini

Spectral Analysis of Qualitative Time Series

David Stoffer

Coherence Consideration in Binary Time Series Analysis

Benjamin Kedem

Discrete-Valued Spatio-Temporal Processes

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

Scott H. Holan and Christopher K. Wikle

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

Christopher K. Wikle and Mevin B. Hooten

Autologistic Regression Models for Spatio-Temporal Binary Data

Jun Zhu and Yanbing Zheng

Spatio-Temporal Modeling for Small Area Health Analysis

Andrew B. Lawson and Ana Corberán-Vallet

Multivariate and Long Memory Discrete-Valued Processes

Models for Multivariate Count Time Series

Dynamic Models for Time Series of Counts with a Marketing Application

Nalini Ravishanker, Rajkumar Venkatesan, and Shan Hu

Long Memory Discrete-Valued Time Series

Robert Lund, Scott H. Holan, and James Livsey.

Notes:

"A Chapman & Hall Book."

Includes bibliographical references at the end of each chapters and index.

Description based on print version record.

ISBN:

0-429-10218-6

1-4665-7774-6

9780429102189

OCLC:

963695984