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lclGWAS (version 1.0.1)

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

Description

The core of this 'Rcpp' based package is several functions to compute the baseline hazard, effect parameter, and frailty variance for the discrete-time shared frailty model with random effects. The core functions include two processes: (1) evaluate the multiple variable integration to compute the exact proportional hazards model based likelihood and (2) estimate desired parameters using maximum likelihood estimation. The integration is evaluated by 'Cuhre' function from 'Cuba' library (Hahn, T., Cuba-a library for multidimensional numerical integration, Comput. Phys. Commun. 168, 2005, 78-95 ), and the source files of 'Cuhre' function are included in this package. Maximization process is carried out using the Brent's algorithm, and the 'C+ +' code file is from John Burkardt and John Denker (Brent, R.,Algorithms for Minimization without Derivatives, Dover, 2002, ISBN 0-486-41998-3).

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Install

install.packages('lclGWAS')

Monthly Downloads

16

Version

1.0.1

License

GPL (>= 2)

Maintainer

Jiaxing Lin

Last Published

November 15th, 2016

Functions in lclGWAS (1.0.1)

lclGWAS-package

Efficient Estimation of Multivariate Frailty Model Using Exact Likelihood Function for Grouped Survival Data
varEst

Estimate the Frailty Variance for Discrete-Time Multivariate Frailty Model for Grouped Survival Data
alphaEst

Estimate the Baseline Hazard for Discrete-Time Multivariate Frailty Model for Grouped Survival Data
betaEst

Estimate the Effect Parameter for Discrete-Time Multivariate Frailty Model for Grouped Survival Data