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kmc
View on CRAN: Click
here
Download and install kmc package within the R console
Install from CRAN:
install.packages("kmc")
Install from Github:
library("remotes")
install_github("cran/kmc")
Install by package version:
library("remotes")
install_version("kmc", "0.4-2")
Attach the package and use:
library("kmc")
Maintained by
Yifan Yang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.kmc . https://github.com/yfyang86/kmc/ . kmc results . kmc.pdf . kmc_0.4-2.tar.gz . kmc_0.4-2.zip . kmc_0.4-2.zip . kmc_0.4-2.zip . kmc_0.4-2.tgz . kmc_0.4-2.tgz . kmc_0.4-2.tgz . kmc_0.4-2.tgz . kmc_0.4-2.tgz . kmc_0.4-2.tgz . kmc archive . https://CRAN.R-project.org/package=kmc .
First Published: 2013-12-25
Latest Update: 2022-11-22
Description:
Given constraints for right censored data, we use a recursive computational algorithm to calculate the the "constrained" Kaplan-Meier estimator. The constraint is assumed given in linear estimating equations or mean functions. We also illustrate how this leads to the empirical likelihood ratio test with right censored data and accelerated failure time model with given coefficients. EM algorithm from emplik package is used to get the initial value. The properties and performance of the EM algorithm is discussed in Mai Zhou and Yifan Yang (2015) and Mai Zhou and Yifan Yang (2017) . More applications could be found in Mai Zhou (2015) .
How to cite:
Yifan Yang (2013). kmc: Kaplan-Meier Estimator with Constraints for Right Censored Data – a Recursive Computational Algorithm. R package version 0.4-2, https://cran.r-project.org/web/packages/kmc. Accessed 12 Apr. 2025.
Previous versions and publish date:
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Other R packages that kmc depends,
imports, suggests or enhances
Complete documentation for kmc
Functions, R codes and Examples using
the kmc R package
Some associated functions: check_G_mat . kmc.bjtest . kmc.clean . kmc.solve . plotkmc .
Some associated R codes: RcppExport.R . kmc.R . kmcmaskel.R . Full kmc package functions and examples
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