violinPlot

An interface to the 'BaM' (Bayesian Modeling) engine,
a 'Fortran'-based executable aimed at estimating a model
with a Bayesian approach and using it for prediction,
with a particular focus on uncertainty quantification.
Classes are defined for the various building blocks of
'BaM' inference (model, data, error models, Markov Chain Monte Carlo (MCMC) samplers, predictions).
The typical usage is as follows:
(1) specify the model to be estimated;
(2) specify the inference setting (dataset, parameters, error models...);
(3) perform Bayesian-MCMC inference;
(4) read, analyse and use MCMC samples;
(5) perform prediction experiments.
Technical details are available (in French) in
Renard (2017) <https://hal.science/hal-02606929v1>.
Examples of applications include
Mansanarez et al. (2019) <doi:10.1029/2018WR023389>,
Le Coz et al. (2021) <doi:10.1002/hyp.14169>,
Perret et al. (2021) <doi:10.1029/2020WR027745>,
Darienzo et al. (2021) <doi:10.1029/2020WR028607> and
Perret et al. (2023) <doi:10.1061/JHEND8.HYENG-13101>.

Benjamin Renard

RBaM

Bayesian Modeling: Estimate a Computer Model and Make Uncertain
Predictions

INRAE 

Ministère de la Transition Ecologique - SCHAPI 

violinPlot function

<dl><dt>sim</dt>
<dd>vector or matrix or data frame, MCMC simulations</dd>
<dt>ylab</dt>
<dd>Character, label of y-axis</dd>
<dt>col</dt>
<dd>Color</dd></dl>

Arguments

violinPlot — violinPlot

<dl>

<dt>sim</dt>
<dd>vector or matrix or data frame, MCMC simulations</dd>


<dt>ylab</dt>
<dd>Character, label of y-axis</dd>


<dt>col</dt>
<dd>Color</dd>

</dl>

violinPlot: violinPlot

Description

Usage

Value

Arguments

Examples