TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 37

SAS/Ets User's Guide 37. 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 | 352 F Chapter 8 The AUTOREG Procedure D number specifies the parameter to determine the radius for BDS test. The BDS test sets up the radius as r D a where a is the standard deviation of the time series to be tested. By default D . PVALUE DIST SIM specifies the way to calculate the p-values. By default or if PVALUE DIST is specified the p-values are calculated according to the asymptotic distribution of BDS statistics that is the standard normal distribution . Otherwise for samples of size less than 500 the p-values are obtained though Monte Carlo simulation. Z value specifies the type of the time series residuals to be tested. The values of the Z suboption are as follows Y specifies the regressand. The default is Z Y. RO specifies the OLS residuals. R specifies the residuals of the final model. RM specifies the structural residuals of the final model. SR specifies the standardized residuals of the final model defined by residuals over the square root of the conditional variance. If BDS is defined without additional suboptions all suboptions are set as default values. That is the statement model return x1 x2 nlag 1 BDS is equivalent to the statement model return x1 x2 nlag 1 BDS M 20 D PVALUE DIST Z Y To do the specification check of a GARCH 1 1 model you can write the SAS statement as follows model return garch p 1 q 1 BDS Z SR CHOW obsi .obSn computes Chow tests to evaluate the stability of the regression coefficient. The Chow test is also called the analysis-of-variance test. Each value obsi listed on the CHOW option specifies a break point of the sample. The sample is divided into parts at the specified break point with observations before obsi in the first part and obsi and later observations in the second part and the fits of the model in the two parts are compared to whether both parts of the sample are consistent with the same model. The break points obsi refer to observations within the time range of the dependent variable ignoring missing values .

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