.beta_mom.NR.fun

First and second derivative of target for mode and variance of proposal

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

.beta_mom.NR.fun function

<dl><dt>df</dt>
<dd>Data frame with indicators</dd>
<dt>k</dt>
<dd>index</dd>
<dt>beta</dt>
<dd>vector of parameters</dd>
<dt>bp</dt>
<dd>number of covariates</dd>
<dt>cprop_beta</dt>
<dd>proposal variance standard deviation</dd></dl>

Arguments

First and second derivative of target for mode and variance of proposal — .beta_mom.NR.fun

<dl>

<dt>df</dt>
<dd>Data frame with indicators</dd>


<dt>k</dt>
<dd>index</dd>


<dt>beta</dt>
<dd>vector of parameters</dd>


<dt>bp</dt>
<dd>number of covariates</dd>


<dt>cprop_beta</dt>
<dd>proposal variance standard deviation</dd>

</dl>

.beta_mom.NR.fun: First and second derivative of target for mode and variance of proposal

Description

Usage

Value

Arguments