JMP 14.0 Online Documentation (English)
Discovering JMP
Using JMP
Basic Analysis
Essential Graphing
Profilers
Design of Experiments Guide
Fitting Linear Models
Predictive and Specialized Modeling
Multivariate Methods
Quality and Process Methods
Reliability and Survival Methods
Consumer Research
Scripting Guide
JSL Syntax Reference
JMP iPad Help
JMP Interactive HTML
Capabilities Index
JMP 13 Online Documentation
JMP 12 Online Documentation
Reliability and Survival Methods
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Fit Parametric Survival
• Nonlinear Parametric Survival Models
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Nonlinear Parametric Survival Models
Use the Nonlinear platform for survival models in the following instances:
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The model is nonlinear.
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You need a distribution other than Weibull, lognormal, exponential, Fréchet, or loglogistic.
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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 the
Predictive and Specialized Modeling
book.
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.
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Help created on 7/12/2018