TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 117

SAS/Ets User's Guide 117. 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 | 1152 F Chapter 18 The MODEL Procedure Distributed Lag Models and the PDL Macro In the following example the variable y is modeled as a linear function of x the first lag of x the second lag of x and so forth yt a boxt biXt-1 b2Xt-2 bjxt-3 . bnXt -n Models of this sort can introduce a great many parameters for the lags and there may not be enough data to compute accurate independent estimates for them all. Often the number of parameters is reduced by assuming that the lag coefficients follow some pattern. One common assumption is that the lag coefficients follow a polynomial in the lag length d bi X j 0 where d is the degree of the polynomial used. Models of this kind are called Almon lag models polynomial distributed lag models or PDLs for short. For example Figure shows the lag distribution that can be modeled with a low-order polynomial. Endpoint restrictions can be imposed on a PDL to require that the lag coefficients be 0 at the 0th lag or at the final lag or at both. Figure Polynomial Distributed Lags For linear single-equation models SAS ETS software includes the PDLREG procedure for estimating PDL models. See Chapter 20 The PDLREG Procedure for a more detailed discussion of polynomial distributed lags and an explanation of endpoint restrictions. Distributed Lag Models and the PDL Macro F 1153 Polynomial and other distributed lag models can be estimated and simulated or forecast with PROC MODEL. For polynomial distributed lags the PDL macro can generate the needed programming statements automatically. The PDL Macro The SAS macro PDL generates the programming statements to compute the lag coefficients of polynomial distributed lag models and to apply them to the lags of variables or expressions. To use the PDL macro in a model program you first call it to declare the lag distribution later you call it again to apply the PDL to a variable or expression. The first call generates a PARMS statement for the polynomial parameters and assignment .

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• Hướng dẫn sử dụng SAS ETS
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• báo cáo tài chính
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