tailieunhanh - SAS/ETS 9.22 User's Guide 77

SAS/Ets User's Guide 77. 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 | 752 F Chapter 13 The ESM Procedure Output Retail Sales Forecast Plots The default simple exponential smoothing model is used because the MODEL option is omitted on the FORECAST statement. Note that for simple exponential smoothing the forecasts are constant. The following ESM procedure statements are identical to the preceding statements except that the PRINT FORECASTS option is specified proc esm data sales out nextyear print forecasts id date interval month forecast _numeric_ run In addition to forecasting each of the monthly time series the preceding statements print the forecasts by using the Output Delivery System ODS the forecasts are partially shown in Output . This output shows the predictions prediction standard errors and the upper and lower confidence limits for the next twelve monthly periods. Example Forecasting of Transactional Data F 753 Output Forecast Tables Shoe Department Sales Obs Time The ESM Procedure Forecasts for Variable shoes Standard Forecasts Error 95 Confidence Limits 62 FEB1999 63 MAR1999 64 APR1999 65 MAY1999 66 JUN1999 67 JUL1999 68 AUG1999 69 SEP1999 70 OCT1999 71 NOV1999 72 DEC1999 73 JAN2000 Example Forecasting of Transactional Data This example illustrates how the ESM procedure can be used to forecast transactional data. The following DATA step creates a data set from data recorded at several Internet Web sites. The data set WEBSITES contains a variable TIME that represents time and the variables ENGINE BOATS CARS and PLANES that