Quality and Reliability Methods - SAS

398 Reliability and Survival Analysis II Chapter 20
Nonlinear Parametric Survival Models
Figure 20.22 Nonlinear Model with Custom Loss Function
The fitting process estimates the parameters by maximizing the negative log of the Weibull likelihood
function.
12. (Optional) Click Confidence Limits to show lower and upper 95% confidence limits for the parameters
in the Solution table. See Figure 20.23.
Figure 20.23 Solution Report
Note: Because the confidence limits are profile likelihood confidence intervals instead of the standard
asymptotic confidence intervals, they can take time to compute.
You can also run the model with the predefined exponential and lognormal loss functions. Before you fit
another model, reset the parameter estimates to the least squares estimates, as they may not converge
otherwise. To reset the parameter estimates:
13. (Optional) From the red triangle menu next to Nonlinear Fit, select Revert to Original Parameters.