Statistical Methods for Forecasting

Bovas Abraham, Johannes Ledolter (Autoren)

Buch | Hardcover

464 Seiten

1983
John Wiley & Sons Inc (Verlag)
978-0-471-86764-7 (ISBN)

Infos

Econometric Analysis by Control Methods Gregory C. Chow Reports on new developments in the techniques and applications of stochastic control in economics that have token place since the author's Analysis and Control of Dynamic Economic Systems (Wiley, 1975). Includes techniques tailored to nonlinear, simultaneous-equation models in economics, and a guide to a computer program for finding optimal control solutions; control techniques for the analysis and formulation of economic policies and the comparison of econometric models; estimation and control of econometric models under the assumption of rational expectations; and the application of stochastic control methods to models in continuous time. 1981 320 pp. Regression Diagnostics Identifying Influential Data and Sources of Collinearity David A. Belsley, Edwin Kuh and Roy E. Welsch Provides practicing statisticians and econometricians with new tools for assessing quality and reliability of regression estimates.
Diagnostic techniques are developed that: aid in the systematic location of data points that are unusual or inordinately influential; measure the presence and intensity of collinear relations among the regression data; help to identify the variables involved in each; pinpoint estimated coefficients that are potentially the most adversely affected. Emphasizes diagnostics and includes suggestions for remedial action. Wiley Series in Probability and Mathematical Statistics. 1980 292 pp. Forecasting with Univariate Box-Jenkins Models Concepts and Cases Alan Pankratz Explains the concepts and use of univariate Box-Jenkins/ARIMA analysis and forecasting through 15 case studies. Cases show how to build good ARIMA models in a step-by-step manner using red data. Also includes examples of model misspecification. Provides guidance to alternative models and discusses reasons for choosing one over another. 1983 560 pp.

Autor

About the authors Bovas Abraham is Associate Professor in the Department of Statistics and Actuarial Science, at the University of Waterloo, Ontario, Canada. He is a member of the American Statistical Association, the American Society for Duality Control, the Canadian Statistical Association and a Fellow of the Royal Statistical Society. Dr. Abraham received his Ph.D. in statistics from the University of Wisconsin, Madison. Johannes Ledolter is an Associate Professor in bath the Deportment of Statistics and Actuarial Science, and the Department of Management Sciences at the University of Iowa. He is a member of the American Statistical Association and a Fellow of the Royal Statistical Society. Dr. Ledolter is also coauthor of Forecasting Using Leading Indicators. He received his Ph.D. in statistics from the University of Wisconsin, Madison.

Inhalt

Introduction and Summary. The Regression Model and Its Application In Forecasting. Regression and Exponential Smoothing Methods to Forecast Non--seasonal Time Series. Regression and Exponential Smoothing Methods to Forecast Seasonal Time Series. Stochastic Time Series Models. Seasonal Autoregressive Integrated Moving Average Models. Relationships Between Forecasts from General Exponential Smoothing and Forecasts from Arima Time Series Models. Special Topics. References. Exercises. Data Appendix. Table Appendix. Index.

Produkt-Details

• Erscheint lt. Verlag: 9.11.1983
• Reihe/Serie: Probability & Mathematical Statistics S.
• Zusatzinfo: illustrations, bibliography, index
• Verlagsort: New York
• Sprache: englisch
• Maße: 160 x 236 mm
• Gewicht: 709 g
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• ISBN-10: 0-471-86764-0 / 0471867640
• ISBN-13: 978-0-471-86764-7 / 9780471867647
• Zustand: Neuware