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| Author | : SAS Institute |
| Publisher | : SAS Institute |
| Total Pages | : 0 |
| Release | : 2009 |
| Genre | : Forecasting |
| ISBN | : 9781599947952 |
Documents the syntax of the SAS High-Performance Forecasting product and demonstrates its use through examples.
| Author | : |
| Publisher | : SAS Institute |
| Total Pages | : 0 |
| Release | : 2006 |
| Genre | : Electronic data processing |
| ISBN | : 9781599941684 |
This guide documents the syntax of the High-Performance Forecasting product and demonstrates its use through examples.
| Author | : |
| Publisher | : Sas Inst |
| Total Pages | : 492 |
| Release | : 2007 |
| Genre | : Computers |
| ISBN | : 9781599945705 |
This guide documents the syntax of the High-Performance Forecasting product and demonstrates its use through examples.
| Author | : SAS Institute |
| Publisher | : Sas Inst |
| Total Pages | : 86 |
| Release | : 2004 |
| Genre | : Computers |
| ISBN | : 9781590472354 |
In virtually all businesses, poor forecasts lead to ill-devised plans, which can result in the loss of business, customers, and market share, as well as an increase in costs. This title guides you through the SAS High-Performance Forecasting product, designed to help your business succeed by translating large amounts of transactional data into more accurate, automatic forecasts on a large scale. High-Performance Forecasting enables you to accumulate the transactional data into time series data, select the appropriate models and generates forecasts of the time series automatically, and perform trend and seasonal analysis on transactional data for millions of variables. You will learn to forecast intermittent time series (slow moving goods) and to address forecast aggregation hierarchies (by-groups). This guide documents the syntax of the High-Performance Forecasting product and demonstrates its use through examples. This title is also available online. This title is designed to help IT professionals and forecasting experts utilize the full analytical sophistication of SAS High-Performance Forecasting for large-scale forecasting projects. Supports releases 9.1 and higher of SAS software.
| Author | : Tim Rey |
| Publisher | : SAS Institute |
| Total Pages | : 336 |
| Release | : 2012-07-02 |
| Genre | : Computers |
| ISBN | : 1612900933 |
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. This book is part of the SAS Press program.
| Author | : Tim Rey |
| Publisher | : SAS Institute |
| Total Pages | : 336 |
| Release | : 2012-07 |
| Genre | : Computers |
| ISBN | : 9781642953008 |
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.
| Author | : Charles W. Chase |
| Publisher | : John Wiley & Sons |
| Total Pages | : 335 |
| Release | : 2009-07-23 |
| Genre | : Business & Economics |
| ISBN | : 0470531010 |
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
| Author | : Harish Gulati |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 299 |
| Release | : 2018-05-30 |
| Genre | : Computers |
| ISBN | : 1788622480 |
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.
| Author | : Michael Gilliland |
| Publisher | : John Wiley & Sons |
| Total Pages | : 435 |
| Release | : 2021-05-11 |
| Genre | : Business & Economics |
| ISBN | : 1119782473 |
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.
| Author | : SAS Institute |
| Publisher | : Sas Inst |
| Total Pages | : 670 |
| Release | : 1999 |
| Genre | : Computers |
| ISBN | : 9781580254892 |
