valid_mcmc

validate the operational parameters for MCMC method

internal

method

A tool which aims to help evaluate the effect of external borrowing using an integrated approach described in Lewis et al., (2019) <doi:10.1080/19466315.2018.1497533> that combines propensity score and Bayesian dynamic borrowing methods.

Isaac Gravestock

psborrow

Bayesian Dynamic Borrowing with Propensity Score

Craig Gower-Page

Matt Secrest

Yichen Lu

Aijing Lin

F. Hoffmann-La Roche AG 

valid_mcmc function

<dl><dt>n.chains</dt>
<dd>number of parallel chains for the model</dd>
<dt>n.adapt</dt>
<dd>number of iterations for adaptation</dd>
<dt>n.burn</dt>
<dd>number of iterations discarded as burn-in</dd>
<dt>n.iter</dt>
<dd>number of iterations to monitor</dd></dl>

Arguments

validate the operational parameters for MCMC method — valid_mcmc

<dl>

<dt>n.chains</dt>
<dd>number of parallel chains for the model</dd>


<dt>n.adapt</dt>
<dd>number of iterations for adaptation</dd>


<dt>n.burn</dt>
<dd>number of iterations discarded as burn-in</dd>


<dt>n.iter</dt>
<dd>number of iterations to monitor</dd>

</dl>

valid_mcmc: validate the operational parameters for MCMC method

Description

Usage

Value

Arguments