TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 122

SAS/Ets User's Guide 122. 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 | 1202 F Chapter 18 The MODEL Procedure Equation variable names can appear in parts of the PROC MODEL printed output and they can be used in the model program. For example RESID-prefixed variables can be used in LAG functions to define equations with moving-average error terms. See the section Autoregressive Moving-Average Error Processes on page 1138 for details. The meaning of these prefixes is detailed in the section Equation Translations on page 1204. Parameters Parameters are variables that have the same value for each observation. Parameters can be given values or can be estimated by fitting the model to data. During the SOLVE stage parameters are treated as constants. If no estimation is performed the SOLVE stage uses the initial value provided in the ESTDATA data set the MODEL file or in the PARAMETER statement as the value of the parameter. The PARAMETERS statement declares the parameters of the model. Parameters are not lagged and they cannot be changed by the model program. Control Variables Control variables supply constant values to the model program that can be used to control the model in various ways. The CONTROL statement declares control variables and specifies their values. A control variable is like a parameter except that it has a fixed value and is not estimated from the data. Control variables are not reinitialized before each pass through the data and can thus be used to retain values between passes. You can use control variables to vary the program logic. Control variables are not affected by lagging functions. For example if you have two versions of an equation for a variable Y you could put both versions in the model and by using a CONTROL statement to select one of them produce two different solutions to explore the effect the choice of equation has on the model as shown in the following statements select case when 1 y .first version of equation. when 2 y .second version of equation. end control case 1 solve out case1 run control case 2 .

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• Hướng dẫn sử dụng SAS ETS
• các mô hình phân tích tài chính
• báo cáo tài chính
• phân tích đầu tư
• phân tích tính khả dụng các khoản đầu tư