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Statistical Methods For Forecasting


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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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