Skip to main content Site map

Introduction to Time Series and Forecasting 3rd ed. 2016


Introduction to Time Series and Forecasting 3rd ed. 2016

Hardback by Brockwell, Peter J.; Davis, Richard A.

Introduction to Time Series and Forecasting

WAS £74.99   SAVE £11.25

£63.74

ISBN:
9783319298528
Publication Date:
31 Aug 2016
Edition/language:
3rd ed. 2016 / English
Publisher:
Springer International Publishing AG
Pages:
425 pages
Format:
Hardback
For delivery:
Estimated despatch 22 - 27 May 2024
Introduction to Time Series and Forecasting

Description

This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Many additional special topics are also covered. New to this edition: A chapter devoted to Financial Time Series Introductions to Brownian motion, Lévy processes and Itô calculus An expanded section on continuous-time ARMA processes

Contents

Introduction.- Stationary Processes.- ARMA Models.- Spectral Analysis.- Modeling and Forecasting with ARMA Processes.- Nonstationary and Seasonal Time Series Models.- Time Series Models for Financial Data.- Multivariate Time Series.- State-Space Models.- Forecasting Techniques.- Further Topics.- Appendix A: Random Variables and Probability Distributions.- Appendix B: Statistical Complements.- Appendix C: Mean Square Convergence.- Appendix D: Lévy Processes, Brownian Motion and Itô Calculus.- Appendix E: An ITSM Tutorial.- References.- Index.

Back

Middlesex University logo