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Forecasting Examples For Business And Economics Using The Sas System
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Book Synopsis Forecasting Examples for Business and Economics Using the SAS System by : SAS Institute
Download or read book Forecasting Examples for Business and Economics Using the SAS System written by SAS Institute and published by Sas Inst. This book was released on 1996 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Economic and Business Forecasting by : John E. Silvia
Download or read book Economic and Business Forecasting written by John E. Silvia and published by John Wiley & Sons. This book was released on 2014-03-10 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the secrets to applying simple econometric techniques to improve forecasting Equipping analysts, practitioners, and graduate students with a statistical framework to make effective decisions based on the application of simple economic and statistical methods, Economic and Business Forecasting offers a comprehensive and practical approach to quantifying and accurate forecasting of key variables. Using simple econometric techniques, author John E. Silvia focuses on a select set of major economic and financial variables, revealing how to optimally use statistical software as a template to apply to your own variables of interest. Presents the economic and financial variables that offer unique insights into economic performance Highlights the econometric techniques that can be used to characterize variables Explores the application of SAS software, complete with simple explanations of SAS-code and output Identifies key econometric issues with practical solutions to those problems Presenting the "ten commandments" for economic and business forecasting, this book provides you with a practical forecasting framework you can use for important everyday business applications.
Book Synopsis SAS for Forecasting Time Series, Third Edition by : John C. Brocklebank, Ph.D.
Download or read book SAS for Forecasting Time Series, Third Edition written by John C. Brocklebank, Ph.D. and published by SAS Institute. This book was released on 2018-03-14 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: To use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject. With this third edition of SAS for Forecasting Time Series, intermediate-to-advanced SAS users—such as statisticians, economists, and data scientists—can now match the most sophisticated forecasting methods to the most current SAS applications. Starting with fundamentals, this new edition presents methods for modeling both univariate and multivariate data taken over time. From the well-known ARIMA models to unobserved components, methods that span the range from simple to complex are discussed and illustrated. Many of the newer methods are variations on the basic ARIMA structures. Completely updated, this new edition includes fresh, interesting business situations and data sets, and new sections on these up-to-date statistical methods: ARIMA models Vector autoregressive models Exponential smoothing models Unobserved component and state-space models Seasonal adjustment Spectral analysis Focusing on application, this guide teaches a wide range of forecasting techniques by example. The examples provide the statistical underpinnings necessary to put the methods into practice. The following up-to-date SAS applications are covered in this edition: The ARIMA procedure The AUTOREG procedure The VARMAX procedure The ESM procedure The UCM and SSM procedures The X13 procedure The SPECTRA procedure SAS Forecast Studio Each SAS application is presented with explanation of its strengths, weaknesses, and best uses. Even users of automated forecasting systems will benefit from this knowledge of what is done and why. Moreover, the accompanying examples can serve as templates that you easily adjust to fit your specific forecasting needs. This book is part of the SAS Press program.
Book Synopsis Forecasting Examples for Business and Econometrics Using the SAS System by :
Download or read book Forecasting Examples for Business and Econometrics Using the SAS System written by and published by . This book was released on 1996 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applied Data Mining for Forecasting Using SAS by : Tim Rey
Download or read book Applied Data Mining for Forecasting Using SAS written by Tim Rey and published by SAS Institute. This book was released on 2012-07 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Data Mining for Forecasting Using SAS, by Tim Rey, Arthur Kordon, and Chip Wells, introduces and describes approaches for mining large time series data sets. Written for forecasting practitioners, engineers, statisticians, and economists, the book details how to select useful candidate input variables for time series regression models in environments when the number of candidates is large, and identifies the correlation structure between selected candidate inputs and the forecast variable. This book is essential for forecasting practitioners who need to understand the practical issues involved in applied forecasting in a business setting. Through numerous real-world examples, the authors demonstrate how to effectively use SAS software to meet their industrial forecasting needs.
Book Synopsis Business Forecasting by : Michael Gilliland
Download or read book Business Forecasting written by Michael Gilliland and published by John Wiley & Sons. This book was released on 2021-05-11 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the role of machine learning and artificial intelligence in business forecasting from some of the brightest minds in the field In Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning accomplished authors Michael Gilliland, Len Tashman, and Udo Sglavo deliver relevant and timely insights from some of the most important and influential authors in the field of forecasting. You'll learn about the role played by machine learning and AI in the forecasting process and discover brand-new research, case studies, and thoughtful discussions covering an array of practical topics. The book offers multiple perspectives on issues like monitoring forecast performance, forecasting process, communication and accountability for forecasts, and the use of big data in forecasting. You will find: Discussions on deep learning in forecasting, including current trends and challenges Explorations of neural network-based forecasting strategies A treatment of the future of artificial intelligence in business forecasting Analyses of forecasting methods, including modeling, selection, and monitoring In addition to the Foreword by renowned researchers Spyros Makridakis and Fotios Petropoulos, the book also includes 16 "opinion/editorial" Afterwords by a diverse range of top academics, consultants, vendors, and industry practitioners, each providing their own unique vision of the issues, current state, and future direction of business forecasting. Perfect for financial controllers, chief financial officers, business analysts, forecast analysts, and demand planners, Business Forecasting will also earn a place in the libraries of other executives and managers who seek a one-stop resource to help them critically assess and improve their own organization's forecasting efforts.
Book Synopsis SAS Programming for Researchers and Social Scientists by : Paul E. Spector
Download or read book SAS Programming for Researchers and Social Scientists written by Paul E. Spector and published by SAGE. This book was released on 2001-04-20 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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." a?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." a?Philip Craiger, Computer Science, University of Nebraska, Omaha ThisA bookA 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." a?James P. Whittenburg, History, College of William & Mary A "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 re
Book Synopsis Demand-Driven Forecasting by : Charles W. Chase
Download or read book Demand-Driven Forecasting written by Charles W. Chase and published by John Wiley & Sons. This book was released on 2009-07-23 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Demand-Driven Forecasting A Structured Approach to Forecasting "There are authors of advanced forecasting books who take an academic approach to explaining forecast modeling that focuses on the construction of arcane algorithms and mathematical proof that are not very useful for forecasting practitioners. Then, there are other authors who take a general approach to explaining demand planning, but gloss over technical content required of modern forecasters. Neither of these approaches is well-suited for helping business forecasters critically identify the best demand data sources, effectively apply appropriate statistical forecasting methods, and properly design efficient demand planning processes. In Demand-Driven Forecasting, Chase fills this void in the literature and provides the reader with concise explanations for advanced statistical methods and credible business advice for improving ways to predict demand for products and services. Whether you are an experienced professional forecasting manager, or a novice forecast analyst, you will find this book a valuable resource for your professional development." —Daniel Kiely, Senior Manager, Epidemiology, Forecasting & Analytics, Celgene Corporation "Charlie Chase has given forecasters a clear, responsible approach for ending the timeless tug of war between the need for 'forecast rigor' and the call for greater inclusion of 'client judgment.' By advancing the use of 'domain knowledge' and hypothesis testing to enrich base-case forecasts, he has empowered professional forecasters to step up and impact their companies' business results favorably and profoundly, all the while enhancing the organizational stature of forecasters broadly." —Bob Woodard, Vice President, Global Consumer and Customer Insights, Campbell Soup Company
Book Synopsis Neural Network Modeling Using SAS Enterprise Miner by : Randall Matignon
Download or read book Neural Network Modeling Using SAS Enterprise Miner written by Randall Matignon and published by AuthorHouse. This book was released on 2005-08 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Predictive Modeling with SAS Enterprise Miner by : Kattamuri S. Sarma
Download or read book Predictive Modeling with SAS Enterprise Miner written by Kattamuri S. Sarma and published by SAS Institute. This book was released on 2017-07-20 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: « Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling. »--
Book Synopsis Data Mining Using SAS Enterprise Miner by : Randall Matignon
Download or read book Data Mining Using SAS Enterprise Miner written by Randall Matignon and published by John Wiley & Sons. This book was released on 2007-08-13 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: The most thorough and up-to-date introduction to data mining techniques using SAS Enterprise Miner. The Sample, Explore, Modify, Model, and Assess (SEMMA) methodology of SAS Enterprise Miner is an extremely valuable analytical tool for making critical business and marketing decisions. Until now, there has been no single, authoritative book that explores every node relationship and pattern that is a part of the Enterprise Miner software with regard to SEMMA design and data mining analysis. Data Mining Using SAS Enterprise Miner introduces readers to a wide variety of data mining techniques and explains the purpose of-and reasoning behind-every node that is a part of the Enterprise Miner software. Each chapter begins with a short introduction to the assortment of statistics that is generated from the various nodes in SAS Enterprise Miner v4.3, followed by detailed explanations of configuration settings that are located within each node. Features of the book include: The exploration of node relationships and patterns using data from an assortment of computations, charts, and graphs commonly used in SAS procedures A step-by-step approach to each node discussion, along with an assortment of illustrations that acquaint the reader with the SAS Enterprise Miner working environment Descriptive detail of the powerful Score node and associated SAS code, which showcases the important of managing, editing, executing, and creating custom-designed Score code for the benefit of fair and comprehensive business decision-making Complete coverage of the wide variety of statistical techniques that can be performed using the SEMMA nodes An accompanying Web site that provides downloadable Score code, training code, and data sets for further implementation, manipulation, and interpretation as well as SAS/IML software programming code This book is a well-crafted study guide on the various methods employed to randomly sample, partition, graph, transform, filter, impute, replace, cluster, and process data as well as interactively group and iteratively process data while performing a wide variety of modeling techniques within the process flow of the SAS Enterprise Miner software. Data Mining Using SAS Enterprise Miner is suitable as a supplemental text for advanced undergraduate and graduate students of statistics and computer science and is also an invaluable, all-encompassing guide to data mining for novice statisticians and experts alike.
Book Synopsis Business Forecasting, Second Edition by : A. Reza Hoshmand
Download or read book Business Forecasting, Second Edition written by A. Reza Hoshmand and published by Routledge. This book was released on 2009-12-04 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book emphasizes the rationale, application, and interpretation of the most commonly used forecasting techniques in business.
Download or read book SAS for Finance written by Harish Gulati and published by Packt Publishing Ltd. This book was released on 2018-05-30 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the analytical power of SAS to perform financial analysis efficiently Key Features Leverage the power of SAS to analyze financial data with ease Find hidden patterns in your data, predict future trends, and optimize risk management Learn why leading banks and financial institutions rely on SAS for financial analysis Book Description SAS is a groundbreaking tool for advanced predictive and statistical analytics used by top banks and financial corporations to establish insights from their financial data. SAS for Finance offers you the opportunity to leverage the power of SAS analytics in redefining your data. Packed with real-world examples from leading financial institutions, the author discusses statistical models using time series data to resolve business issues. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate financial models. You can easily assess the pros and cons of models to suit your unique business needs. By the end of this book, you will be able to leverage the true power of SAS to design and develop accurate analytical models to gain deeper insights into your financial data. What you will learn Understand time series data and its relevance in the financial industry Build a time series forecasting model in SAS using advanced modeling theories Develop models in SAS and infer using regression and Markov chains Forecast inflation by building an econometric model in SAS for your financial planning Manage customer loyalty by creating a survival model in SAS using various groupings Understand similarity analysis and clustering in SAS using time series data Who this book is for Financial data analysts and data scientists who want to use SAS to process and analyze financial data and find hidden patterns and trends from it will find this book useful. Prior exposure to SAS will be helpful but is not mandatory. Some basic understanding of the financial concepts is required.
Book Synopsis Applied Economic Forecasting using Time Series Methods by : Eric Ghysels
Download or read book Applied Economic Forecasting using Time Series Methods written by Eric Ghysels and published by Oxford University Press. This book was released on 2018-03-23 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic forecasting is a key ingredient of decision making both in the public and in the private sector. Because economic outcomes are the result of a vast, complex, dynamic and stochastic system, forecasting is very difficult and forecast errors are unavoidable. Because forecast precision and reliability can be enhanced by the use of proper econometric models and methods, this innovative book provides an overview of both theory and applications. Undergraduate and graduate students learning basic and advanced forecasting techniques will be able to build from strong foundations, and researchers in public and private institutions will have access to the most recent tools and insights. Readers will gain from the frequent examples that enhance understanding of how to apply techniques, first by using stylized settings and then by real data applications--focusing on macroeconomic and financial topics. This is first and foremost a book aimed at applying time series methods to solve real-world forecasting problems. Applied Economic Forecasting using Time Series Methods starts with a brief review of basic regression analysis with a focus on specific regression topics relevant for forecasting, such as model specification errors, dynamic models and their predictive properties as well as forecast evaluation and combination. Several chapters cover univariate time series models, vector autoregressive models, cointegration and error correction models, and Bayesian methods for estimating vector autoregressive models. A collection of special topics chapters study Threshold and Smooth Transition Autoregressive (TAR and STAR) models, Markov switching regime models, state space models and the Kalman filter, mixed frequency data models, nowcasting, forecasting using large datasets and, finally, volatility models. There are plenty of practical applications in the book and both EViews and R code are available online at authors' website.
Book Synopsis Applied Data Mining by : Paolo Giudici
Download or read book Applied Data Mining written by Paolo Giudici and published by John Wiley & Sons. This book was released on 2005-09-27 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining can be defined as the process of selection, explorationand modelling of large databases, in order to discover models andpatterns. The increasing availability of data in the currentinformation society has led to the need for valid tools for itsmodelling and analysis. Data mining and applied statistical methodsare the appropriate tools to extract such knowledge from data.Applications occur in many different fields, including statistics,computer science, machine learning, economics, marketing andfinance. This book is the first to describe applied data mining methodsin a consistent statistical framework, and then show how they canbe applied in practice. All the methods described are eithercomputational, or of a statistical modelling nature. Complexprobabilistic models and mathematical tools are not used, so thebook is accessible to a wide audience of students and industryprofessionals. The second half of the book consists of nine casestudies, taken from the author's own work in industry, thatdemonstrate how the methods described can be applied to realproblems. Provides a solid introduction to applied data mining methods ina consistent statistical framework Includes coverage of classical, multivariate and Bayesianstatistical methodology Includes many recent developments such as web mining,sequential Bayesian analysis and memory based reasoning Each statistical method described is illustrated with real lifeapplications Features a number of detailed case studies based on appliedprojects within industry Incorporates discussion on software used in data mining, withparticular emphasis on SAS Supported by a website featuring data sets, software andadditional material Includes an extensive bibliography and pointers to furtherreading within the text Author has many years experience teaching introductory andmultivariate statistics and data mining, and working on appliedprojects within industry A valuable resource for advanced undergraduate and graduatestudents of applied statistics, data mining, computer science andeconomics, as well as for professionals working in industry onprojects involving large volumes of data - such as in marketing orfinancial risk management.
Book Synopsis Business Forecasting by : John E. Hanke
Download or read book Business Forecasting written by John E. Hanke and published by . This book was released on 1998 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: Appropriate for junior/senior and graduate level courses in Forecasting found in Economics or Statistics departments. This top-selling text presents, in a straightforward, application-driven manner, the basic statistical techniques that are useful for preparing individual business forecasts and long-range plans. The emphasis is on the application of techniques by managers for decision-making.
Author :Clive William John Granger Publisher :Emerald Group Pub Limited ISBN 13 :9780122951848 Total Pages :338 pages Book Rating :4.9/5 (518 download)
Book Synopsis Forecasting Economic Time Series by : Clive William John Granger
Download or read book Forecasting Economic Time Series written by Clive William John Granger and published by Emerald Group Pub Limited. This book was released on 1986 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to the theory of time series; Spectral analysis; Building linear time series models; The theory of forecasting; Practical methods for univariate time series forecasting; Forecasting from regression models; Multiple series modeling and forecasting; Building multiple time serie forecasting models; The combination and evaluation of forecasts; Further topics.
