lclGWAS: Efficient Estimation of Discrete-Time Multivariate Frailty Model Using Exact Likelihood Function for Grouped Survival Data
Version 1.0.3

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 ), and the source files of the 'Cuhre' function are included in this package. The maximization process is carried out using Brent's 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).

Package details

AuthorJiaxing Lin, Alexander Sibley, Tracy Truong, Nancy Cox, Eileen Dolan, Yu Jiang, Janice McCarthy, Andrew Allen, Kouros Owzar, Zhiguo Li
Date of publication2017-02-21 00:03:26
MaintainerJiaxing Lin <jiaxing.lin@duke.edu>
LicenseGPL (>= 2)
Version1.0.3
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("lclGWAS")

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lclGWAS documentation built on May 30, 2017, 5:51 a.m.