Forecasting Examples For Business And Economics Using The Sas System
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Forecasting Examples for Business and Economics Using the SAS System
Numerous step-by-step examples show you--the economist, business forecaster, student, or researcher--how to use SAS to generate forecasts for a variety of business and economic data. Examples are based on both time series models and econometric models. You'll learn how to use SAS to forecast time series data using Box-Jenkins ARIMA methodology; develop and forecast transfer functions and intervention models; fit and forecast regression models with autocorrelated, heteroskedastic, and ARCH-GARCH error terms; estimate nonlinear regression models; create forecast confidence limits using Monte Carlo simulation; and more! The main focus of the book is on the code-based procedures in SAS/ETS software, but this book also provides an introduction to the interactive Time Series Forecasting System, and it shows how to plot data and forecasts with SAS/GRAPH software.
SAS Programming for Researchers and Social Scientists
Second Edition SAS® PROGRAMMING FOR RESEARCHERS AND SOCIAL SCIENTISTS By PAUL E. SPECTOR, University of South Florida University of South Florida "Just what the novice SAS programmer needs, particularly those who have no real programming experience. For example, branching is one of the more difficult programming commands for students to implement and the author does an excellent job of explaining this topic clearly and at a basic level. A big plus is the Common Errors section since students will definitely encounter errors." --Robert Pavur, Management Science, University of North Texas The book that won accolades from thousands has been completely revised! Taking a problem solving approach that focuses on common programming tasks that social scientists encounter in doing data analysis, Spector uses sample programs and examples from social science problems to show readers how to write orderly programs and avoid excessive and disorganized branching. He provides readers with a three-step approach (preplanning, writing the program, and debugging) and tips about helpful features and practices as well as how to avoid certain pitfalls. "Spector has done an excellent job in explaining a somewhat difficult topic in a clear and concise manner. I like the fact that screen captures are included. It allows students to better follow what is being described in the book in relation to what is on the screen." --Philip Craiger, Computer Science, University of Nebraska, Omaha This book provides readers with even more practical tips and advice. New features in this edition include: *New sections on debugging in each chapter that provide advice about common errors *End of chapter Debugging Exercises that offer readers the chance to practice spotting the errors in the sample programs *New section in Chapter 1 on how to use the interface, including how to work with three separate windows, where to write the program, executing the program, managing the program files, and using the F key *Five new appendices, including a Glossary of Programming Terms, A Summary of SAS Language Statements, A Summary of SAS PROCs, Information Sources for SAS PROCs, and Corrections for the Debugging Exercises *Plus, a link to Spector′s online SAS course! Appropriate for readers with little or no knowledge of the SAS language, this book will enable readers to run each example, adapt the examples to real problems that the reader may have, and create a program. "A solid introduction to programming in SAS, with a good, brief explanation of how that process differs from the usual point-and-click of Windows-based software such as SPSS and a spreadsheet. Even uninformed students can use it as a guide to creating SAS datasets, manipulating them, and writing programs in the SAS language that will produce all manner of statistical results." --James P. Whittenburg, History, College of William & Mary "Bridges the gap between programming syntax and programming applications. In contrast to other books on SAS programming, this book combines a clear explanation of the SAS language with a problem-solving approach to writing a SAS program. It provides the novice programmer with a useful and meaningful model for solving the types of programming problems encountered by researchers and social scientists." --John E. Cornell, Biostatistician, Audie L. Murphy Memorial Hospital
Neural Network Modeling Using SAS Enterprise Miner
This book is designed in making statisticians, researchers, and programmers aware of the awesome new product now available in SAS called Enterprise Miner. The book will also make readers get familiar with the neural network forecasting methodology in statistics. One of the goals to this book is making the powerful new SAS module called Enterprise Miner easy for you to use with step-by-step instructions in creating a Enterprise Miner process flow diagram in preparation to data-mining analysis and neural network forecast modeling. Topics discussed in this book An overview to traditional regression modeling. An overview to neural network modeling. Numerical examples of various neural network designs and optimization techniques. An overview to the powerful SAS product called Enterprise Miner. An overview to the SAS neural network modeling procedure called PROC NEURAL. Designing a SAS Enterprise Miner process flow diagram to perform neural network forecast modeling and traditional regression modeling with an explanation to the various configuration settings to the Enterprise Miner nodes used in the analysis. Comparing neural network forecast modeling estimates with traditional modeling estimates based on various examples from SAS manuals and literature with an added overview to the various modeling designs and a brief explanation to the SAS modeling procedures, option statements, and corresponding SAS output listings.