tracePlot

2DO (adapt from STooDs): Generate pdf report files summarizing mcmc samples

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 

tracePlot function

<dl><dt>sim</dt>
<dd>vector or matrix or data frame, MCMC simulations</dd>
<dt>ylab</dt>
<dd>Character, label of y-axis to be used if sim has no names</dd>
<dt>keep</dt>
<dd>Integer vector, indices of samples to be kept in cooked MCMC sample</dd>
<dt>col</dt>
<dd>Color</dd>
<dt>psize</dt>
<dd>Numeric, point size</dd></dl>

Arguments

MCMC reporting — tracePlot

<dl>

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


<dt>ylab</dt>
<dd>Character, label of y-axis to be used if sim has no names</dd>


<dt>keep</dt>
<dd>Integer vector, indices of samples to be kept in cooked MCMC sample</dd>


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


<dt>psize</dt>
<dd>Numeric, point size</dd>

</dl>

tracePlot: MCMC reporting

Description

Usage

Value

Arguments

Details

Examples