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lclGWAS  

Efficient Estimation of Discrete-Time Multivariate Frailty Model Using Exact Likelihood Function for Grouped Survival Data
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("lclGWAS", "1.0.3")



Attach the package and use:
library("lclGWAS")
Maintained by
Jiaxing Lin
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-11-15
Latest Update: 2023-01-24
Description:
The core of this Rcpp based package is several functions to estimate the baseline hazard frailty variance and fixed effect parameter for a discrete-time shared frailty model with random effects. The functions are designed to analyze grouped time-to-event data accounting for family structure of related individuals i.e. trios. The core functions include two processes 1 evaluate the multivariable integration to compute the exact proportional hazards model based likelihood and 2 estimate the desired parameters using maximum likelihood estimation. The integration is evaluated by the Cuhre algorithm from the Cuba library Hahn T. Cuba-a library for multidimensional numerical integration Comput. Phys. Commun. 168 2005 78-95 doi10.1016j.cpc.2005.01.010 and the source files of the Cuhre function are included in this package. The maximization process is carried out using Brents algorithm with the C code file from John Burkardt and John Denker Brent R.Algorithms for Minimization without Derivatives Dover 2002 ISBN 0-486-41998-3.
How to cite:
Jiaxing Lin (2016). lclGWAS: Efficient Estimation of Discrete-Time Multivariate Frailty Model Using Exact Likelihood Function for Grouped Survival Data. R package version 1.0.3, https://cran.r-project.org/web/packages/lclGWAS. Accessed 03 Apr. 2025.
Previous versions and publish date:
1.0.1 (2016-11-15 19:35), 1.0.2 (2016-11-30 20:03), 1.0.3 (2017-02-21 00:03), 1.0 (2016-11-15 00:18)
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