priors_distribution.survFit

Return a <code>data.frame</code> with priors distribution of parameters used in
<code>object</code>.

Advanced methods for a valuable quantitative environmental risk
assessment using Bayesian inference of survival and reproduction Data. Among
others, it facilitates Bayesian inference of the general unified
threshold model of survival (GUTS). See our companion paper
Baudrot and Charles (2021) <doi:10.21105/joss.03200>,
as well as complementary details in Baudrot et al. (2018)
<doi:10.1021/acs.est.7b05464> and Delignette-Muller et al.
(2017) <doi:10.1021/acs.est.6b05326>.

Virgile Baudrot

morse

Modelling Reproduction and Survival Data in Ecotoxicology

Sandrine Charles

Marie Laure Delignette-Muller

Wandrille Duchemin

Benoit Goussen

Nils Kehrein

Guillaume Kon-Kam-King

Christelle Lopes

Philippe Ruiz

Alexander Singer

Philippe Veber

priors_distribution.survFit function

<dl><dt>object</dt>
<dd>An object of class <code>survFit</code>.</dd>
<dt>size_sample</dt>
<dd>Size of the random generation of the distribution.
Default is <code>1e3</code>.</dd>
<dt>EFSA_name</dt>
<dd>If <code>TRUE</code>, replace the current terminology by
the one used in the recent EFSA PPR Scientific Opinion (2018).</dd>
<dt>...</dt>
<dd>Further arguments to be passed to generic methods.</dd></dl>

Arguments

Density distribution of priors from a survFit object. — priors_distribution.survFit

<dl>

<dt>object</dt>
<dd>An object of class <code>survFit</code>.</dd>


<dt>size_sample</dt>
<dd>Size of the random generation of the distribution.
Default is <code>1e3</code>.</dd>


<dt>EFSA_name</dt>
<dd>If <code>TRUE</code>, replace the current terminology by
the one used in the recent EFSA PPR Scientific Opinion (2018).</dd>


<dt>...</dt>
<dd>Further arguments to be passed to generic methods.</dd>

</dl>

Density distribution of priors from a <code>survFit</code> object.

priors_distribution.survFit: Density distribution of priors from a `survFit` object.

Description

Usage

Value

Arguments

References