McmcOptions-class

.McmcOptions

Class for the three canonical MCMC options

classes

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.

Daniel Sabanes Bove

crmPack

Object-Oriented Implementation of CRM Designs

Wai Yin Yeung

Giuseppe Palermo

Thomas Jaki

McmcOptions-class function

<dl>
<dt><code>iterations</code></dt>
<dd>number of MCMC iterations</dd></dl>
<dt><code>burnin</code></dt>
<dd>number of burn-in iterations which are not saved</dd>
<dt><code>step</code></dt>
<dd>only every step-th iteration is saved after the burn-in</dd>

Slots

Class for the three canonical MCMC options — McmcOptions-class

<dl>
<dt><code>iterations</code></dt>
<dd>number of MCMC iterations</dd>


<dt><code>burnin</code></dt>
<dd>number of burn-in iterations which are not saved</dd>


<dt><code>step</code></dt>
<dd>only every step-th iteration is saved after the burn-in</dd>


</dl>

McmcOptions-class: Class for the three canonical MCMC options

Description

Arguments

Slots

Examples