print.RoBSA

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.RoBSA function

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

Arguments

Prints a fitted RoBSA object — print.RoBSA

<dl>

<dt>x</dt>
<dd>a fitted RoBSA object.</dd>


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

</dl>

Prints a fitted RoBSA object

print.RoBSA: Prints a fitted RoBSA object

Description

Usage

Value

Arguments

See Also