TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 95

SAS/Ets User's Guide 95. 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 | 932 F Chapter 17 The MDC Procedure Syntax MDC Procedure The MDC procedure is controlled by the following statements PROC MDC options MDCDATA options BOUNDS boundl bound2. BY variables CLASS options ID variable MODEL dependent variables regressors options NEST LEVEL value values @ value . values @ value NLOPTIONS options OUTPUT options RESTRICT restriction1 restriction2 . . . TEST options UTILITY U variables . U variables Functional Summary Table summarizes the statements and options used with the MDC procedure. Table MDC Functional Summary Description Statement Option Data Set Options Formats the data for use by PROC MDC MDCDATA Specifies the input data set MDC DATA Specifies the output data set for CLASS STATEMENT CLASS OUT Writes parameter estimates to an output data set MDC OUTEST Includes covariances in the OUTEST data set MDC COVOUT Writes linear predictors and predicted probabilities to an output data set OUTPUT OUT Declaring the Role of Variables Specifies the ID variable ID Specifies BY-group processing variables BY Printing Control Options Requests all printing options MODEL ALL Displays correlation matrix of the estimates MODEL CORRB Displays covariance matrix of the estimates MODEL COVB Displays detailed information about optimization iterations MODEL ITPRINT Functional Summary F 933 Description Statement Option Suppresses all displayed output MODEL NOPRINT Model Estimation Options Specifies the choice variables MODEL CHOICE Specifies the convergence criterion MODEL CONVERGE Specifies the type of covariance matrix MODEL COVEST Specifies the starting point of the Halton sequence MODEL HALTONSTART Specifies options specific to the HEV model MODEL HEV Sets the initial values of parameters used by the MODEL INITIAL iterative optimization algorithm Specifies the maximum number of iterations MODEL MAXITER Specifies the options specific to mixed logit MODEL MIXED Specifies the number of choices for each person MODEL NCHOICE Specifies the number of .

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