Weib.reg.Frank

See Section 2.6.3 of Emura et al. (2019).

 regression

 Frank copula 

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) <doi:10.1016/j.csda.2010.03.013> for details.

Takeshi Emura

Copula.surv

Analysis of Bivariate Survival Data Based on Copulas

Weib.reg.Frank function

<dl> <dt>x.obs</dt>
<dd>censored times for X</dd> <dt>y.obs</dt>
<dd>censored times for Y</dd> <dt>dx</dt>
<dd>censoring indicators for X</dd> <dt>dy</dt>
<dd>censoring indicators for Y</dd> <dt>zx</dt>
<dd>matrix of covariates for X</dd> <dt>zy</dt>
<dd>matrix of covariates for Y</dd> <dt>convergence.par</dt>
<dd>if TRUE, show the details</dd></dl>

Arguments

Author

Weibull regression under the Frank copula — Weib.reg.Frank

<dl>

 <dt>x.obs</dt>
<dd>censored times for X</dd>

 <dt>y.obs</dt>
<dd>censored times for Y</dd>

 <dt>dx</dt>
<dd>censoring indicators for X</dd>

 <dt>dy</dt>
<dd>censoring indicators for Y</dd>

 <dt>zx</dt>
<dd>matrix of covariates for X</dd>

 <dt>zy</dt>
<dd>matrix of covariates for Y</dd>

 <dt>convergence.par</dt>
<dd>if TRUE, show the details</dd>

</dl>

Weib.reg.Frank: Weibull regression under the Frank copula

Description

Usage

Value

Arguments

Author

Details

References

Examples