TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 152

SAS/Ets User's Guide 152. 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 | 1502 F Chapter 22 The SEVERITY Procedure Experimental Figure P-P Plots for the Lognormal and Weibull Models Fitted to Truncated and Censored Data An Example with Left-Truncation and Right-Censoring F 1503 Figure continued Specifying Initial Values for Parameters All the predefined distributions have parameter initialization functions built into them. For the current example Figure shows the initial values that are obtained by the predefined method for the Burr distribution. It also shows the summary of the optimization process and the final parameter estimates. Figure Burr Model Summary for the Truncated and Censored Data Initial Parameter Values and Bounds for Burr Distribution Parameter Initial Value Lower Bound Upper Bound Theta Infty Alpha Infty Gamma Infty 1504 F Chapter 22 The SEVERITY Procedure Experimental Figure continued Optimization Summary for Burr Distribution Optimization Technique Number of Iterations Number of Function Evaluations Log Likelihood Trust Region 8 21 Parameter Estimates for Burr Distribution Standard Approx Parameter Estimate Error t Value Pr t Theta .0001 Alpha Gamma .0001 You can specify a different set of initial values if estimates are available from fitting the distribution to similar data. For this example the parameters of the Burr distribution can be initialized with the final parameter estimates of the Burr distribution that were obtained in the first example shown in Figure . One of the ways in which you can specify the initial values is as follows ------- Specifying initial values using INIT option -------------- proc severity data test_sev2 print all plots none model y lt threshold rc iscens 1 crit aicc dist burr init theta alpha gamma run The names of the parameters specified in the INIT option must match the names used in the .

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