represents the symbolic survival model obtained from functions like SurvivalModelFit.


SurvivalModel
represents the symbolic survival model obtained from functions like SurvivalModelFit.
Details and Options

- Properties of a survival model are obtained from SurvivalModel[…]["property"].
- SurvivalModel[…][{prop1,prop2,…}] gives several properties.
- SurvivalModel[…][x1,…] gives the value of the best-fit function at a particular point x1, … .
- Normal gives the expression for the default fitted function in a SurvivalModel.
- SurvivalModel objects are returned by fitting functions such as SurvivalModelFit.
- SurvivalModel[…][prop,ann] gives the annotation ann associated with the property prop.
- Possible properties available for a given type of fitted model are listed on the pages for functions such as SurvivalModelFit that generate the model.
- SurvivalModel takes the following options:
-
ConfidenceLevel 95/100 level to use for intervals and bands » ConfidenceRange All range for simultaneous confidence bands » ConfidenceTransform "LogLog" confidence transform to use »
Examples
open all close allBasic Examples (1)
Create a SurvivalModel from some right-censored data:
Extract a property from the model:
Evaluate the survival function at :
Use Normal to obtain the survival function:
Scope (5)
Extract a property from a SurvivalModel object:
The standard errors for the survival function:
Evaluate the fitted function at a point:
Options (7)
ConfidenceLevel (3)
Set the confidence level used for computing confidence intervals and bands:
A set of 90% intervals corresponding to the time points in the model:
The confidence level can also be set before the model has been fitted:
By default the confidence level is set to :
Compute confidence intervals for the survival probability at a point:
Confidence intervals about the survival function at for a range of confidence levels:
ConfidenceRange (1)
ConfidenceTransform (3)
Apply transformations to confidence intervals and bands:
A collection of named transforms:
"LogLog" bands and intervals are used by default:
Transformations can ensure that intervals and bands are appropriately bounded:
Notice that the upper 95% limit is larger than for some event times:
Using a "LogLog" transform corrects this issue:
Define custom transformations:
Explicit definitions for the various named transforms:
Verify that the definitions are equivalent to the named transforms:
History
Text
Wolfram Research (2012), SurvivalModel, Wolfram Language function, https://reference.wolfram.com/language/ref/SurvivalModel.html.
CMS
Wolfram Language. 2012. "SurvivalModel." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/SurvivalModel.html.
APA
Wolfram Language. (2012). SurvivalModel. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/SurvivalModel.html
BibTeX
@misc{reference.wolfram_2025_survivalmodel, author="Wolfram Research", title="{SurvivalModel}", year="2012", howpublished="\url{https://reference.wolfram.com/language/ref/SurvivalModel.html}", note=[Accessed: 16-August-2025]}
BibLaTeX
@online{reference.wolfram_2025_survivalmodel, organization={Wolfram Research}, title={SurvivalModel}, year={2012}, url={https://reference.wolfram.com/language/ref/SurvivalModel.html}, note=[Accessed: 16-August-2025]}