SAS/Ets User's Guide 120. 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 | 1182 F Chapter 18 The MODEL Procedure Figure Solve Step Summary Output The MODEL Procedure Model Summary Model Variables 1 Parameters 3 Equations 1 Number of Statements 1 Program Lag Length 1 Model Variables LHUR Parameters Value a b -0 478849 c Equations LHUR The second page of output shown in Figure gives more information on the failed observation. Figure Solve Step Error Message The MODEL Procedure Dynamic Single-Equation Forecast ERROR Solution values are missing because of missing input values for observation 144 at NEWTON iteration 0. NOTE Additional information on the values of the variables at this observation which may be helpful in determining the cause of the failure of the solution process is printed below. Observation 144 Iteration 0 CC Missing 1 Iteration Errors - Missing. The MODEL Procedure Dynamic Single-Equation Forecast --- Listing of Program Data Vector --- _N_ 144 . . IP . LHUR . a b c NOTE Simulation aborted. From the program data vector you can see the variable IP is missing for observation 144. LHUR could not be computed so the simulation aborted. The solution summary table is shown in Figure . Solution Mode Output F 1183 Figure Solution Summary Report The MODEL Procedure Dynamic Single-Equation Forecast Data Set Options DATA OUT SIM Solution Summary Variables Solved 1 Forecast Lag Length 1 Solution Method NEWTON CONVERGE 1E-8 Maximum CC 0 Maximum Iterations 1 Total Iterations 143 Average Iterations 1 Observations Processed Read 145 Lagged 1 Solved 143 First 2 Last 145 Failed 1 Variables Solved For LHUR This solution summary table includes the names of the input data set and the output data set followed by a description of the model. The table also indicates that the solution method defaulted to Newton s method. The remaining output is defined as follows. Maximum CC is the maximum convergence value .
