Introduction to Time Series Analysis and Forecasting, Solutions ManualISBN: 9780470435748
88 pages
March 2009

Analyzing timeoriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the basic concepts of time series analysis and forecasting. Introduction to Time Series Analysis and Forecasting presents the time series analysis branch of applied statistics as the underlying methodology for developing practical forecasts, and it also bridges the gap between theory and practice by equipping readers with the tools needed to analyze timeoriented data and construct useful, short to mediumterm, statistically based forecasts.
Seven easytofollow chapters provide intuitive explanations and indepth coverage of key forecasting topics, including:

Regressionbased methods, heuristic smoothing methods, and general time series models

Basic statistical tools used in analyzing time series data

Metrics for evaluating forecast errors and methods for evaluating and tracking forecasting performance over time

Crosssection and time series regression data, least squares and maximum likelihood model fitting, model adequacy checking, prediction intervals, and weighted and generalized least squares

Exponential smoothing techniques for time series with polynomial components and seasonal data

Forecasting and prediction interval construction with a discussion on transfer function models as well as intervention modeling and analysis

Multivariate time series problems, ARCH and GARCH models, and combinations of forecasts
The ARIMA model approach with a discussion on how to identify and fit these models for nonseasonal and seasonal time series
The intricate role of computer software in successful time series analysis is acknowledged with the use of Minitab, JMP, and SAS software applications, which illustrate how the methods are implemented in practice. An extensive FTP site is available for readers to obtain data sets, Microsoft Office PowerPoint slides, and selected answers to problems in the book. Requiring only a basic working knowledge of statistics and complete with exercises at the end of each chapter as well as examples from a wide array of fields, Introduction to Time Series Analysis and Forecasting is an ideal text for forecasting and time series courses at the advanced undergraduate and beginning graduate levels. The book also serves as an indispensable reference for practitioners in business, economics, engineering, statistics, mathematics, and the social, environmental, and life sciences.