tailieunhanh - SAS/ETS 9.22 User's Guide 240

SAS/Ets User's Guide 240. 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 | 2382 F Chapter 34 The X12 Procedure Example Setting Regression Parameters This example illustrates the use of fixed regression parameters in PROC X12. Suppose that you have the same data set as in the section Basic Seasonal Adjustment on page 2298. You can specify the following statements to use TRAMO to automatically identify a model that includes a . Census Bureau Easter 25 regressor title Estimate Easter 25 Parameter proc x12 data sales date date MdlInfoOut mdlout1 var sales regression predefined easter 25 automdl run The displayed results are shown in Output . Output Automatic Model ID with Easter 25 Regression Estimate Easter 25 Parameter The X12 Procedure Regression Model Parameter Estimates For Variable sales Standard Type Parameter NoEst Estimate Error t Value Pr t Easter Easter 25 Est Exact ARMA Maximum Likelihood Estimation For Variable sales Standard Parameter Lag Estimate Error t Value Pr t Nonseasonal AR 1 .0001 2 3 Nonseasonal MA 1 .0001 Seasonal MA 12 The MDLINFOOUT data set mdlout1 that contains the model and parameter estimates is shown in Output . proc print data mdlout1 run Example Setting Regression Parameters F 2383 Output MDLINFOOUT Data Set Estimation of Automatic Model ID with Easter 25 Regression Estimate Easter 25 Parameter M M C O O O P D D M A E E P R L L O M D V N T P N T S A A Y A E Y V L O M P R N P A U b E E T T E R E s 1 sales REG PREDEFINED SCALE EASTER EASTER 25 2 sales ARIMA FORECAST NONSEASONAL DIF sales . 3 sales ARIMA FORECAST SEASONAL DIF sales . 4 sales ARIMA FORECAST NONSEASONAL AR sales . 5 sales ARIMA FORECAST NONSEASONAL AR sales . 6 sales ARIMA FORECAST NONSEASONAL AR sales . 7 sales ARIMA FORECAST NONSEASONAL MA sales . 8 sales ARIMA FORECAST SEASONAL MA sales . F S T P S A S N T V V TS L C H O D A A AC A T L IE E E L L TO B