Use the Nonlinear platform for survival models in the following instances:
• The model is nonlinear.
• You need a distribution other than Weibull, lognormal, exponential, Fréchet, loglogistic, SEV, normal, LEV, or logistic.
• You have censoring that is not the usual right, left, or interval censoring.
With the ability to estimate parameters in specified loss functions, the Nonlinear platform becomes a powerful tool for fitting maximum likelihood models. For complete information about the Nonlinear platform, see Nonlinear Regression in Predictive and Specialized Modeling.
To fit a nonlinear model when data are censored, you must first use the formula editor to create a parametric equation that represents a loss function adjusted for censored observations. Then use the Nonlinear platform to estimate the parameters using maximum likelihood.