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. An Introduction to Discrete-Valued Time Series 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.

This book:

• 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

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.