TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 76

SAS/Ets User's Guide 76. 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 | 742 F Chapter 13 The ESM Procedure Note Even if all of the observed data are nonmissing the ACCUMULATE option can create missing values in the accumulated series when the data contain no observations for some of the time periods specified by the INTERVAL option . Forecasting Once the model parameters are estimated one-step-ahead forecasts are generated for the full range of the accumulated and optionally transformed time series data and multistep forecasts are generated from the end of the time series to the future time period specified by the LEAD option. If there are missing values at the end of the time series the forecast horizon will be greater than that specified by the LEAD option. Inverse Transformations If the TRANSFORM option is specified in the FORECAST statement the forecasts of the transformed time series are inverse transformed. By default forecasts of the mean expected value are generated. If the MEDIAN option is specified median forecasts are generated. See Chapter 46 Forecasting Process Details for more details about forecasting transformed time series. Statistics of Fit The statistics of fit are computed by comparing the time series data after accumulation and missing value recoding if specified with the generated forecasts. If the TRANSFORM option is specified the statistics of fit are based on the inverse transformed forecasts. See Chapter 46 Forecasting Process Details for more details about statistics of fit for forecasting models. Forecast Summation The multistep forecasts generated by the preceding steps can optionally be summed from the STARTSUM value to the LEAD value. For example if the options STARTSUM 4 and LEAD 6 are specified on the PROC ESM statement the four-step through six-step ahead forecasts are summed. The forecasts are simply summed however the prediction error variance of this sum is computed by taking into account the correlation between the individual predictions. These variance-related computations are performed only when

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