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frailtyMMpen
View on CRAN: Click
here
Download and install frailtyMMpen package within the R console
Install from CRAN:
install.packages("frailtyMMpen")
Install from Github:
library("remotes")
install_github("cran/frailtyMMpen") Install by package version:
library("remotes")
install_version("frailtyMMpen", "1.2.1") Attach the package and use:
library("frailtyMMpen")
Maintained by
Yunpeng Zhou
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-03-24
Latest Update: 2023-08-08
Description:
The penalized and non-penalized Minorize-Maximization (MM) method for frailty models to fit the clustered data, multi-event data and recurrent data. Least absolute shrinkage and selection operator (LASSO), minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) penalized functions are implemented. All the methods are computationally efficient. These general methods are proposed based on the following papers,
Huang, Xu and Zhou (2022) ,
Huang, Xu and Zhou (2023) .
How to cite:
Yunpeng Zhou (2023). frailtyMMpen: Efficient Algorithm for High-Dimensional Frailty Model. R package version 1.2.1, https://cran.r-project.org/web/packages/frailtyMMpen. Accessed 09 Mar. 2026.
Previous versions and publish date:
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Complete documentation for frailtyMMpen
Functions, R codes and Examples using
the frailtyMMpen R package
Some associated functions: cluster . coef.fpen . event . frailtyMM . frailtyMMpen . hdCLdata . plot.fmm . plot.fpen . predict.fmm . predict.fpen . print.fmm . print.fpen . simdataCL . simdataME . simdataRE . summary.fmm .
Some associated R codes: RcppExports.R . backtrackerror.R . coef.R . fcollect.R . frailtyMM.R . frailtyMMcal.R . frailtyMMpen.R . plot.R . predict.R . print.R . simdata.R . summary.R . zzz.R . Full frailtyMMpen package functions and examples
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