print.summary.RoBSA

Prints summary object for RoBSA method

A framework for estimating ensembles of parametric survival models
with different parametric families. The RoBSA framework uses Bayesian
model-averaging to combine the competing parametric survival models into
a model ensemble, weights the posterior parameter distributions based on
posterior model probabilities and uses Bayes factors to test for the
presence or absence of the individual predictors or preference for a
parametric family (Bartoš, Aust & Haaf, 2022, <doi:10.1186/s12874-022-01676-9>).
The user can define a wide range of informative priors for all parameters
of interest. The package provides convenient functions for summary, visualizations,
fit diagnostics, and prior distribution calibration.

Franti<c5><a1>ek Barto<c5><a1>

RoBSA

Robust Bayesian Survival Analysis

František Bartoš

Julia M. Haaf

Matthew Denwood

Martyn Plummer

print.summary.RoBSA function

<dl><dt>x</dt>
<dd>a summary of a RoBSA object</dd>
<dt>...</dt>
<dd>additional arguments</dd></dl>

Arguments

Prints summary object for RoBSA method — print.summary.RoBSA

<dl>

<dt>x</dt>
<dd>a summary of a RoBSA object</dd>


<dt>...</dt>
<dd>additional arguments</dd>

</dl>

print.summary.RoBSA: Prints summary object for RoBSA method

Description

Usage

Value

Arguments

See Also