Principles of Forecasting


Book Description

This handbook summarises knowledge from experts and empirical studies. It provides guidelines that can be applied in fields such as economics, sociology, and psychology. Includes a comprehensive forecasting dictionary.




Forecasting: principles and practice


Book Description

Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.




Forecasting


Book Description




Computational Science - ICCS 2003. Part 4.


Book Description

The four-volume set LNCS 2657, LNCS 2658, LNCS 2659, and LNCS 2660 constitutes the refereed proceedings of the Third International Conference on Computational Science, ICCS 2003, held concurrently in Melbourne, Australia and in St. Petersburg, Russia in June 2003. The four volumes present more than 460 reviewed contributed and invited papers and span the whole range of computational science, from foundational issues in computer science and algorithmic mathematics to advanced applications in virtually all application fields making use of computational techniques. These proceedings give a unique account of recent results in the field.




Handbook of Research Methods in Tourism


Book Description

'This is an excellent book which significantly contributes to tourism research and education. It takes a rigorous yet readable style to address twenty five of the most pertinent quantitative and qualitative techniques applied in tourism research. the book will appeal to a wider readership of social scientists as well as to scholars of tourism as each chapter provides a thorough overview and explanation of the techniques irrespective of their tourism application.' – Dimitrios Buhalis, Bournemouth University, UK This insightful book explores the most important established and emerging qualitative and quantitative research methods in tourism. the authors provide a detailed overview of the nature of the research method, its use in tourism, the advantages and limitations, and future directions for research. Each chapter is structured to provide information on: the nature of the technique and its evolution; background and types of problems that the technique is designed to handle; applications of the technique to tourism, including discussion of studies that have used the technique and their findings; advantages and limitations of the technique conceptually and for policy formulation; and further developments and applications of the technique in tourism research. Handbook of Research Methods in Tourism will appeal to social scientists, students as well as researchers in tourism who use quantitative and qualitative research techniques.




Advances in Tourism Economics


Book Description

'Advances in Tourism Economics' follows his predecessor 'Advances in Modern Tourism Research' (2007) in providing a thorough assessment of state-of-the-art economic research in this rapidly developing field. The authors start by analyzing the recent upsurge of model-based economic research in the field, which builds on powerful tools in quantitative economics, such as discrete choice models, social accounting matrices, data envelopment analyses, impact assessment models or partial computable equilibrium models including environmental externalities. The volume originates from this novel research spirit in the area and aims to offer an attractive collection of operational research tools and approaches. It forms an appealing record of modern tourism economics and positions the field within the strong tradition of quantitative economic research, with due attention for both the demand and supply side of the tourism sector, including technological and logistic advances.




Statistical Methods for Forecasting


Book Description

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This book, it must be said, lives up to the words on its advertising cover: 'Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.' It does just that!" -Journal of the Royal Statistical Society "A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series analysis by PhD students; or to support a concentration in quantitative methods for MBA students; or as a work in applied statistics for advanced undergraduates." -Choice Statistical Methods for Forecasting is a comprehensive, readable treatment of statistical methods and models used to produce short-term forecasts. The interconnections between the forecasting models and methods are thoroughly explained, and the gap between theory and practice is successfully bridged. Special topics are discussed, such as transfer function modeling; Kalman filtering; state space models; Bayesian forecasting; and methods for forecast evaluation, comparison, and control. The book provides time series, autocorrelation, and partial autocorrelation plots, as well as examples and exercises using real data. Statistical Methods for Forecasting serves as an outstanding textbook for advanced undergraduate and graduate courses in statistics, business, engineering, and the social sciences, as well as a working reference for professionals in business, industry, and government.




Business Forecasting


Book Description

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.