TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 32

SAS/Ets User's Guide 32. 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 | 302 F Chapter 7 The ARIMA Procedure proc arima data air Identify and seasonally difference ozone series identify var ozone 12 crosscorr x1 12 summer winter noprint Fit a multiple regression with a seasonal MA model by the maximum likelihood method estimate q 1 12 input x1 summer winter noconstant method ml Forecast forecast lead 12 id date interval month run The ESTIMATE statement results are shown in Output and Output . Output Parameter Estimates Intervention Data for Ozone Concentration Box and Tiao JASA 1975 Parameter Estimate The ARIMA Procedure Maximum Likelihood Estimation Standard Approx Error t Value Pr t Lag Variable Shift MA1 1 .0001 1 ozone 0 MA2 1 .0001 12 ozone 0 NUM1 .0001 0 x1 0 NUM2 .0001 0 summer 0 NUM3 0 winter 0 Variance Estimate Std Error Estimate AIC SBC Number of Residuals 204 Output Model Summary Model for variable ozone Period s of Differencing 12 Moving Average Factors Factor 1 1 B 1 Factor 2 1 - B 12 Example Using Diagnostics to Identify ARIMA Models F 303 Output continued Input Number 1 Input Variable x1 Period s of Differencing 12 Overall Regression Factor The FORECAST statement results are shown in Output . Output Forecasts Forecasts for variable ozone Obs Forecast Std Error 95 Confidence Limits 217 218 219 220 221 222 223 224 225 226 227 228 Example Using Diagnostics to Identify ARIMA Models Fitting ARIMA models is as much an art as it is a science. The ARIMA procedure has

• Tài chính doanh nghiệp
• 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