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SAS/ETS 9.22 User's Guide 74

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SAS/Ets 9.22 User's Guide 74. Provides detailed reference material for using SAS/ETS software and guides you through the analysis and forecasting of features such as univariate and multivariate time series, cross-sectional time series, seasonal adjustments, multiequational nonlinear models, discrete choice models, limited dependent variable models, portfolio analysis, and generation of financial reports, with introductory and advanced examples for each procedure. You can also find complete information about two easy-to-use point-and-click applications: the Time Series Forecasting System, for automatic and interactive time series modeling and forecasting, and the Investment Analysis System, for time-value of money analysis of a variety of investments | 722 F Chapter 12 The ENTROPY Procedure Experimental References Coleman J. S. Campbell E. Q. Hobson C. J. McPartland J. Mood A. M. Weinfeld F. D. and York R. L. 1966 Equality of Educational Opportunity Washington DC U.S. Government Printing Office. Deaton A. and Muellbauer J. 1980 An Almost Ideal Demand System The American Economic Review 70 312-326. Golan A. Judge G. and Miller D. 1996 Maximum Entropy Econometrics Robust Estimation with Limited Data Chichester England John Wiley Sons. Golan A. Judge G. and Perloff J. 1996 A Generalized Maximum Entropy Approach to Recovering Information from Multinomial Response Data Journal of the American Statistical Association 91 841-853. Golan A. Judge G. and Perloff J. 1997 Estimation and Inference with Censored and Ordered Multinomial Response Data Journal of Econometrics 79 23-51. Golan A. Judge G. and Perloff J. 2002 Comparison of Maximum Entropy and Higher-Order Entropy Estimators Journal of Econometrics 107 195-211. Good I. J. 1963 Maximum Entropy for Hypothesis Formulation Especially for Multidimensional Contingency Tables Annals of Mathematical Statistics 34 911-934. Harmon A. M. Preckel P. and Eales J. 1998 Maximum Entropy-Based Seemingly Unrelated Regression Master s thesis Purdue University. Jaynes E. T. 1957 Information of Theory and Statistical Mechanics Physics Review 106 620-630. Jaynes E. T. 1963 Information Theory and Statistical Mechanics in K. W. Ford ed. Brandeis Lectures in Theoretical Physics volume 3 Statistical Physics 181-218 New York Amsterdam W. A. Benjamin Inc. Kapur J. N. and Kesavan H. K. 1992 Entropy Optimization Principles with Applications Boston Academic Press. Kullback J. 1959 Information Theory and Statistics New York John Wiley Sons. Kullback J. and Leibler R. A. 1951 On Information and Sufficiency Annals of Mathematical Statistics. LaMotte L. R. 1994 A Note on the Role of Independence in t Statistics Constructed from Linear Statistics in Regression Models The American Statistician 48 .