## CRAN

# lclGWAS 1.0.3

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

Released Feb 21, 2017 by Jiaxing Lin

### Dependencies

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

## Installation

### Maven

This package can be included as a dependency from a Java or Scala project by including
the following your project's `pom.xml`

file.
Read more
about embedding Renjin in JVM-based projects.

<dependencies> <dependency> <groupId>org.renjin.cran</groupId> <artifactId>lclGWAS</artifactId> <version>1.0.3-b24</version> </dependency> </dependencies> <repositories> <repository> <id>bedatadriven</id> <name>bedatadriven public repo</name> <url>https://nexus.bedatadriven.com/content/groups/public/</url> </repository> </repositories>

### Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:

library('org.renjin.cran:lclGWAS')

## Test Results

This package was last tested against Renjin 0.9.2689 on Aug 26, 2018.