Learn R Programming

Copula.surv (version 3.0)

Analysis of Bivariate Survival Data Based on Copulas

Description

Simulating bivariate survival data from copula models. Estimation of the association parameter in copula models. Two different ways to estimate the association parameter in copula models are implemented. A goodness-of-fit test for a given copula model is implemented. See Emura, Lin and Wang (2010) for details.

Copy Link

Version

Install

install.packages('Copula.surv')

Monthly Downloads

300

Version

3.0

License

GPL-2

Maintainer

Takeshi Emura

Last Published

December 16th, 2025

Functions in Copula.surv (3.0)

Weib.reg.cBB1.0

Weibull regression under the conditional BB1 copula with known "delta"

Weibull regression under the conditional BB1 copula

Simulating data from the BB1 copula regression model

Simulating data from the BB1 copula

Simulating data from the Gumbel-Barnett (GB) copula

Simulating data from the Gumbel copula

Weib.reg.Gumbel

Weibull regression under the Gumbel copula

Simulating data from the t-copula

Weibull regression under the Frank copula

Simulating data from the Joe copula

Simulating data from the Clayton copula

Estimation of an association parameter via the pseudo-likelihood

Copula.surv-package

Analysis of Bivariate Survival Data

Estimation of an association parameter via the unweighted estimator

Weibull regression under the BB1 copula

Weibull regression under the BB1 copula with known "delta"

Weib.reg.Clayton

Weibull regression under the Clayton copula

Simulating data from the Celebioglu-Cuadras (CC) copula

Estimation of an association parameter via the unweighted estimator

A goodness-of-fit test for the Gumbel copula

A goodness-of-fit test for the Clayton copula

Estimation of an association parameter via the pseudo-likelihood

Simulating data from the FGM copula

Simulating data from the Frank copula