Time Series Analysis and Forecasting by Example

Description

An intuition-based approach enables you to master time series analysis with ease Time Series Analysis and Forecasting by Example provides the fundamental techniques in time series analysis using various examples. By introducing necessary theory through examples that showcase the discussed topics, the authors successfully help readers develop an intuitive understanding of seemingly complicated time series models and their implications. The book presents methodologies for time series analysis in a simplified, example-based approach. Using graphics, the authors discuss each presented example in detail and explain the relevant theory while also focusing on the interpretation of results in data analysis. Following a discussion of why autocorrelation is often observed when data is collected in time, subsequent chapters explore related topics, including: Graphical tools in time series analysis Procedures for developing stationary, non-stationary, and seasonal models How to choose the best time series model Constant term and cancellation of terms in ARIMA models Forecasting using transfer function-noise models The final chapter is dedicated to key topics such as spurious relationships, autocorrelation in regression, and multiple time series. Throughout the book, real-world examples illustrate step-by-step procedures and instructions using statistical software packages such as SAS®, JMP, Minitab, SCA, and R. A related Web site features PowerPoint slides to accompany each chapter as well as the book's data sets. With its extensive use of graphics and examples to explain key concepts, Time Series Analysis and Forecasting by Example is an excellent book for courses on time series analysis at the upper-undergraduate and graduate levels. it also serves as a valuable resource for practitioners and researchers who carry out data and time series analysis in the fields of engineering, business, and economics.

Get the book

Amazon.com

Search the book

eBay.com

Search the book

Other editions

• 

  Time Series Analysis and Forecasting by Example

  • 2011-08-09
  • - pages
  • Paperback
  • John Wiley & Sons

Similar books

• 

  Introduction to Time Series Analysis and Forecasting

  By Douglas C. Montgomery, Cheryl L. Jennings, Murat Kulahci

  The book also serves as an indispensablereference for practitioners in business, economics, engineering, statistics, mathematics, and the social, environmental, and life sciences.

• 

  Forecasting and Time Series Analysis

  By Douglas C. Montgomery, Lynwood A. Johnson, John S. Gardiner

  This practical, user-oriented second edition describes how to use statistical modeling and analysis methods for forecasting and prediction problems. Statistical and mathematical terms are introduced only as they are needed,...

• 

  Time Series Analysis: Forecasting and Control

  By George E. P. Box, Gwilym M. Jenkins, Gregory C. Reinsel

  [a,] 0.[a,] 1 Pl Al-->e |# = — – E. |: # ==#E |: ". 2 Cy o: t=1 Cl the information matrix for (q), 6) for the mixed ARMA model is –2 Cl (7.2.17) /v1_–2 U/UU/V I(p,0) = EIX'Xla," – E |yu vy a that is, y,(0) y,(1) : y (p − 1) Y. (0) yu ...

• 

  Hands-On Time Series Analysis with R: Perform time series analysis and forecasting using R

  By Rami Krispin

  These insights and patterns can then be utilized to explore past events and forecast future values in the series. This book explores the basics of time series analysis with R and lays the foundations you need to build forecasting models.

• 

  Introduction to Time Series Analysis and Forecasting

  By Douglas C. Montgomery, Cheryl L. Jennings, Murat Kulahci

  The book is also an excellent reference for practitioners and researchers who need to model and analyze time series data to generate forecasts.

• 

  Forecasting: principles and practice

  By Rob J Hyndman, George Athanasopoulos

  Forecasting is required in many situations.

• 

  Applied Time Series: Analysis and Forecasting

  By T. M. J. A. Cooray

  Applied Time Series: Analysis and Forecasting provides the theories, methods and tools for necessary modeling and forecasting of time series. It includes a complete theoretical development of univariate time series...

• 

  Practical Time Series Analysis: Prediction with Statistics and Machine Learning

  By Aileen Nielsen

  Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and ...

• 

  Time-Series Forecasting

  By Chris Chatfield

  From the author of the bestselling "Analysis of Time Series," Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods.

• 

  Applied Time Series Analysis and Forecasting with Python

  By Changquan Huang, Alla Petukhina

  Primarily intended for students of statistics, economics and data science with an undergraduate knowledge of probability and statistics, the book will equally appeal to industry professionals in the fields of artificial intelligence and ...