Statistical Methods Forecasting by Abraham Bovas (35 results)

Hardback. Condition: Fair. 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.…

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Hardcover. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Hardcover. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Condition: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.…

Condition: Good. Good condition. A copy that has been read but remains intact. May contain markings such as bookplates, stamps, limited notes and highlighting, or a few light stains.

Hardback. Condition: Fair. 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.…

Condition: Very Good. 1st Edition. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Condition: Very Good. 1st Edition. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. …

Hardcover. Condition: New. 1st Edition. pre owned, shelved perused; 443pp all new all clean; navy linen covers; I ship daily at 0900 CT IL USA.

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Hardcover. First Edition; First Printing. Very Good+ in a Very Good+ dust jacket.; 9.3 X 6.3 X 1.1 inches; 464 pages.

hardcover. Condition: New. In shrink wrap. Looks like an interesting title.

hardcover. Condition: Gut. 445 Seiten; 9780471867647.3 Gewicht in Gramm: 1.

Condition: New.

Paperback. Condition: new. Paperback. 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. This book provides statistical methods and models that can be used to produce short-term forecasts. The authors provide an intermediate-level discussion of a variety of statistical forecasting methods and models, to explain their interconnections, and to bridge the gap between theory and practice. . Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: As New. Unread book in perfect condition.

Paperback. Condition: new. Paperback. 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. This book provides statistical methods and models that can be used to produce short-term forecasts. The authors provide an intermediate-level discussion of a variety of statistical forecasting methods and models, to explain their interconnections, and to bridge the gap between theory and practice. . Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Condition: New.

Condition: New. In English.

Paperback. Condition: new. Paperback. 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. This book provides statistical methods and models that can be used to produce short-term forecasts. The authors provide an intermediate-level discussion of a variety of statistical forecasting methods and models, to explain their interconnections, and to bridge the gap between theory and practice. . Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.

Condition: New. pp. xv + 445 Illus.

Condition: New. This book provides statistical methods and models that can be used to produce short-term forecasts. The authors provide an intermediate-level discussion of a variety of statistical forecasting methods and models, to explain their interconnections, and to bridge the gap between theory and practice. . Series: Wiley Series in Probability and Statistics. Num Pages: 472 pages, black & white illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 229 x 156 x 28. Weight in Grams: 676. . 2005. 2nd. Paperback. . . . .…

Condition: New. pp. xv + 445.