.set_hyperparameters

Allows Bayesian borrowing from a historical dataset for time-to-
event data. A flexible baseline hazard function is achieved via a piecewise
exponential likelihood with time varying split points and smoothing prior on the
historic baseline hazards. The method is described in Scott and Lewin (2024)
<doi:10.48550/arXiv.2401.06082>, and the software paper is in Axillus et al.
(2024) <doi:10.48550/arXiv.2408.04327>.

Darren Scott

BayesFBHborrow

Bayesian Dynamic Borrowing with Flexible Baseline Hazard
Function

Sophia Axillus

.set_hyperparameters function

<dl><dt>hyperparameters</dt>
<dd>list of hyperparameters, could contain any combination
of the listed hyperparameters</dd>
<dt>model_choice</dt>
<dd>choice of model, could be either of 'mix', 'uni' or 'all'</dd></dl>

Arguments

Set tuning parameters — .set_hyperparameters

<dl>

<dt>hyperparameters</dt>
<dd>list of hyperparameters, could contain any combination
of the listed hyperparameters</dd>


<dt>model_choice</dt>
<dd>choice of model, could be either of 'mix', 'uni' or 'all'</dd>

</dl>

.set_hyperparameters: Set tuning parameters

Description

Usage

Value

Arguments