Reliability and Survival Methods > Fit Parametric Survival > Nonlinear Parametric Survival Models
Publication date: 08/13/2020

Nonlinear Parametric Survival Models

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.

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).
.