TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 87

SAS/Ets User's Guide 87. 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 | 852 F Chapter 15 The FORECAST Procedure OUTEST Data Set The FORECAST procedure writes the parameter estimates and goodness-of-fit statistics to an output data set when the OUTEST option is specified. The OUTEST data set contains the following variables the BY variables the first ID variable which contains the value of the ID variable for the last observation in the input data set used to fit the model _TYPE_ a character variable that identifies the type of each observation the VAR statement variables which contain statistics and parameter estimates for the input series. The values contained in the VAR statement variables depend on the _TYPE_ variable value for the observation. The observations contained in the OUTEST data set are identified by the _TYPE_ variable. The OUTEST data set might contain observations with the following _TYPE_ values AR1-ARn The observation contains estimates of the autoregressive parameters for the series. Two-digit lag numbers are used if the value of the NLAGS option is 10 or more in that case these _TYPE_ values are AR01-AR . These observations are output for the STEPAR method only. CONSTANT The observation contains the estimate of the constant or intercept parameter for the time trend model for the series. For the exponential smoothing and the Winters methods the trend model is centered that is t 0 at the last observation used for the fit. LINEAR The observation contains the estimate of the linear or slope parameter for the time trend model for the series. This observation is output only if you specify TREND 2 or TREND 3. N The observation contains the number of nonmissing observations used to fit the model for the series. QUAD The observation contains the estimate of the quadratic parameter for the time trend model for the series. This observation is output only if you specify TREND 3. SIGMA The observation contains the estimate of the standard deviation of the error term for the series. S1-S3 The observations contain exponentially .

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• Hướng dẫn sử dụng SAS ETS
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• báo cáo tài chính
• phân tích đầu tư
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