.mu_update

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

.mu_update function

<dl><dt>Sigma_s</dt>
<dd>VCV matrix (j + 1) x (j + 1).</dd>
<dt>lambda_0</dt>
<dd>Baseline hazard.</dd>
<dt>sigma2</dt>
<dd>Scale variance.</dd>
<dt>J</dt>
<dd>Number of split point.</dd></dl>

Arguments

Calculate mu posterior update — .mu_update

<dl>

<dt>Sigma_s</dt>
<dd>VCV matrix (j + 1) x (j + 1).</dd>


<dt>lambda_0</dt>
<dd>Baseline hazard.</dd>


<dt>sigma2</dt>
<dd>Scale variance.</dd>


<dt>J</dt>
<dd>Number of split point.</dd>

</dl>

.mu_update: Calculate mu posterior update

Description

Usage

Value

Arguments