TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 110

SAS/Ets User's Guide 110. 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 | 1082 F Chapter 18 The MODEL Procedure Figure Diagnostics for Convergence Failure The MODEL Procedure OLS Estimation ERROR The parameter estimates failed to converge for OLS after 100 iterations using CONVERGE as the convergence criteria. The MODEL Procedure OLS Estimation N Iteration N Obs R Objective Subit a b c OLS 100 20 2 Gauss Method Parameter Change Vector a b c By using the default starting values PROC MODEL is unable to take even the first step in iterating to the solution. The change in the parameters that the Gauss-Newton method computes is very extreme and makes the objective values worse instead of better. Even when this step is shortened by a factor of a million the objective function is still worse and PROC MODEL is unable to estimate the model parameters. The problem is caused by the starting value of C. Using the default starting value C the first iteration attempts to compute better values of A and B by what is in effect a linear regression of Y on the 10 000th root of X which is almost the same as the constant 1. Thus the matrix that is inverted to compute the changes is nearly singular and affects the accuracy of the computed parameter changes. This is also illustrated by the next part of the output which displays collinearity diagnostics for the crossproducts matrix of the partial derivatives with respect to the parameters shown in Figure . Figure Collinearity Diagnostics Collinearity Diagnostics Condition --------Proportion of Variation---- Number Eigenvalue Number a b c 1 2 3 1187758 This output shows that the matrix is singular and that the partials of A B and C with respect to the residual are collinear at the point in the parameter space. See the section Linear Dependencies on page 1091 for a full explanation of the .

• Tài chính doanh nghiệp
• Hướng dẫn sử dụng SAS ETS
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• báo cáo tài chính
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