Implements a wide range of model-based dose
escalation designs, ranging from classical and modern continual
reassessment methods (CRMs) based on dose-limiting toxicity endpoints to
dual-endpoint designs taking into account a biomarker/efficacy outcome. The
focus is on Bayesian inference, making it very easy to setup a new design
with its own JAGS code. However, it is also possible to implement 3+3
designs for comparison or models with non-Bayesian estimation. The whole
package is written in a modular form in the S4 class system, making it very
flexible for adaptation to new models, escalation or stopping rules.

Object-Oriented Implementation of CRM Designs

package-ubuntu-20.04-r-4.0.5#cran#crmPack-1.0.0

<p>The random generation of the Inverse gamma distribution
</p>

<table summary="R argblock">
<tr valign="top">
<td><code>n</code></td>
<td>
<p>the number of observations</p>
</td>
</tr>
<tr valign="top">
<td><code>a</code></td>
<td>
<p>the shape parameter of the inverse gamma distribution</p>
</td>
</tr>
<tr valign="top">
<td><code>b</code></td>
<td>
<p>the scale parameter of the inverse gamm distribution</p>
</td>
</tr>
</table>

package-ubuntu-20.04-r-4.0.5#cran#crmPack-1.0.0#docs#rinvGamma

rinvGamma

Description

Usage

Arguments

crmPack

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`n`	the number of observations
`a`	the shape parameter of the inverse gamma distribution
`b`	the scale parameter of the inverse gamm distribution