ilap

Computes the inverse Laplace transform for gamma frailty simulation.

Implementation of various statistical models for multivariate
event history data <doi:10.1007/s10985-013-9244-x>. Including multivariate
cumulative incidence models <doi:10.1002/sim.6016>, and bivariate random
effects probit models (Liability models) <doi:10.1016/j.csda.2015.01.014>.
Modern methods for survival analysis, including regression modelling (Cox, Fine-Gray,
Ghosh-Lin, Binomial regression) with fast computation of influence functions.

Klaus Holst

mets

Analysis of Multivariate Event Times

Klaus K. Holst

Thomas Scheike 

ilap function

<dl><dt>theta</dt>
<dd>frailty parameter.</dd>
<dt>t</dt>
<dd>value at which to evaluate.</dd></dl>

Arguments

Inverse Laplace Transform Helper — ilap

<dl>

<dt>theta</dt>
<dd>frailty parameter.</dd>


<dt>t</dt>
<dd>value at which to evaluate.</dd>

</dl>

ilap: Inverse Laplace Transform Helper

Description

Usage

Value

Arguments