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SurvMA  

Model Averaging Prediction of Personalized Survival Probabilities
View on CRAN: Click here


Download and install SurvMA package within the R console
Install from CRAN:
install.packages("SurvMA")

Install from Github:
library("remotes")
install_github("cran/SurvMA")

Install by package version:
library("remotes")
install_version("SurvMA", "1.6.8")



Attach the package and use:
library("SurvMA")
Maintained by
Mengyu Li
[Scholar Profile | Author Map]
First Published: 2024-09-23
Latest Update: 2024-09-23
Description:
Provide model averaging-based approaches that can be used to predict personalized survival probabilities. The key underlying idea is to approximate the conditional survival function using a weighted average of multiple candidate models. Two scenarios of candidate models are allowed: (Scenario 1) partial linear Cox model and (Scenario 2) time-varying coefficient Cox model. A reference of the underlying methods is Li and Wang (2023) <doi:10.1016/j.csda.2023.107759>.
How to cite:
Mengyu Li (2024). SurvMA: Model Averaging Prediction of Personalized Survival Probabilities. R package version 1.6.8, https://cran.r-project.org/web/packages/SurvMA. Accessed 21 Feb. 2025.
Previous versions and publish date:
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Complete documentation for SurvMA
Functions, R codes and Examples using the SurvMA R package
Full SurvMA package functions and examples
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