SurvIT_cst

Survival function for "IT" model with external concentration changing
with time

Advanced methods for a valuable quantitative environmental risk
assessment using Bayesian inference of survival Data with toxicokinetics
toxicodynamics (TKTD) models. Among others, it facilitates Bayesian inference of
the general unified threshold model of survival (GUTS). See models description
in Jager et al. (2011) <doi:10.1021/es103092a> and implementation
using Bayesian inference in Baudrot and Charles (2019)
<doi:10.1038/s41598-019-47698-0>.

Virgile Baudrot

morseTKTD

Bayesian Inference of TKTD Models

Sandrine Charles

Marie Laure Delignette-Muller

Benoit Goussen

Nils Kehrein

Guillaume Kon-Kam-King

Christelle Lopes

Alexander Singer

Philippe Veber

SurvIT_cst function

<dl><dt>Cw</dt>
<dd>A vector of external concentration</dd>
<dt>time</dt>
<dd>A vector of time</dd>
<dt>kd</dt>
<dd>a vector of parameter</dd>
<dt>hb</dt>
<dd>a vector of parameter</dd>
<dt>alpha</dt>
<dd>a vector of parameter</dd>
<dt>beta</dt>
<dd>a vector of parameter</dd>
<dt>interpolate_length</dt>
<dd>can be used to provide a sequence from 0 to maximum of
the time of exposure in original dataset (used for fitting).</dd></dl>

Arguments

Internal predict function — SurvIT_cst

<dl>

<dt>Cw</dt>
<dd>A vector of external concentration</dd>


<dt>time</dt>
<dd>A vector of time</dd>


<dt>kd</dt>
<dd>a vector of parameter</dd>


<dt>hb</dt>
<dd>a vector of parameter</dd>


<dt>alpha</dt>
<dd>a vector of parameter</dd>


<dt>beta</dt>
<dd>a vector of parameter</dd>


<dt>interpolate_length</dt>
<dd>can be used to provide a sequence from 0 to maximum of
the time of exposure in original dataset (used for fitting).</dd>

</dl>

Internal predict function

SurvIT_cst: Internal predict function

Description

Usage

Value

Arguments