An introduction to discrete-valued time series / Christian Weiss.

Format:

Book

Author/Creator:

Weiss, Christian H., 1977- author.

Language:

English

Subjects (All):

Time-series analysis.

Discrete-time systems--Mathematical models.

Discrete-time systems.

Physical Description:

1 online resource (1 volume) : illustrations

Edition:

1st edition

Place of Publication:

Hoboken, New Jersey : Wiley, 2018.

System Details:

text file

Summary:

A much-needed introduction to the field of discrete-valued time series, with a focus on count-data time series Time series analysis is an essential tool in a wide array of fields, including business, economics, computer science, epidemiology, finance, manufacturing and meteorology, to name just a few. Despite growing interest in discrete-valued time series—especially those arising from counting specific objects or events at specified times—most books on time series give short shrift to that increasingly important subject area. This book seeks to rectify that state of affairs by providing a much needed introduction to discrete-valued time series, with particular focus on count-data time series. The main focus of this book is on modeling. Throughout numerous examples are provided illustrating models currently used in discrete-valued time series applications. Statistical process control, including various control charts (such as cumulative sum control charts), and performance evaluation are treated at length. Classic approaches like ARMA models and the Box-Jenkins program are also featured with the basics of these approaches summarized in an Appendix. In addition, data examples, with all relevant R code, are available on a companion website. Provides a balanced presentation of theory and practice, exploring both categorical and integer-valued series Covers common models for time series of counts as well as for categorical time series, and works out their most important stochastic properties Addresses statistical approaches for analyzing discrete-valued time series and illustrates their implementation with numerous data examples Covers classical approaches such as ARMA models, Box-Jenkins program and how to generate functions Includes dataset examples with all necessary R code provided on a companion website An Introduction to Discrete-Valued Time Series is a valuable working resource for researchers and practitioners in a broad range of fields, including statistics, data science, machine learning, and engineering. It will also be of interest to postgraduate students in statistics, mathematics and economics.

Contents:

A first approach for modeling time series of counts : the thinning-based INAR (1) model

Further thinning-based models for count time series

INGARCH models for count time series

Further models for count time series

Analyzing categorical time series

Models for categorical time series

Control charts for count processes

Control charts for categorical processes.

Notes:

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9781119096986

1119096987

9781119097013

1119097010

OCLC:

1004957494