ggs_rocplot

Receiver-Operator Characteristic (ROC) plot for models with binary outcomes

Tools for assessing and diagnosing convergence of
Markov Chain Monte Carlo simulations, as well as for graphically display
results from full MCMC analysis. The package also facilitates the graphical
interpretation of models by providing flexible functions to plot the
results against observed variables, and functions to work with
hierarchical/multilevel batches of parameters
(Fernández-i-Marín, 2016 <doi:10.18637/jss.v070.i09>).

Xavier i Marín

ggmcmc

Tools for Analyzing MCMC Simulations from Bayesian Inference

Xavier Fernández i Marín

ggs_rocplot function

<dl><dt>D</dt>
<dd>Data frame whith the simulations. Notice that only the posterior outcomes are needed, and so either the previous call to ggs() should have limited the family of parameters to pass to the predicted outcomes.</dd>
<dt>outcome</dt>
<dd>vector (or matrix or array) containing the observed outcome variable. Currently only a vector is supported.</dd>
<dt>fully_bayesian</dt>
<dd>logical, false by default. When not fully Bayesian, it uses the median of the predictions for each observation by iteration. When TRUE the function plots as many ROC curves as iterations. It uses a a lot of CPU and needs more memory. Use it with caution.</dd></dl>

Arguments

Receiver-Operator Characteristic (ROC) plot for models with binary outcomes — ggs_rocplot

<dl>

<dt>D</dt>
<dd>Data frame whith the simulations. Notice that only the posterior outcomes are needed, and so either the previous call to ggs() should have limited the family of parameters to pass to the predicted outcomes.</dd>


<dt>outcome</dt>
<dd>vector (or matrix or array) containing the observed outcome variable. Currently only a vector is supported.</dd>


<dt>fully_bayesian</dt>
<dd>logical, false by default. When not fully Bayesian, it uses the median of the predictions for each observation by iteration. When TRUE the function plots as many ROC curves as iterations. It uses a a lot of CPU and needs more memory. Use it with caution.</dd>

</dl>

ggs_rocplot: Receiver-Operator Characteristic (ROC) plot for models with binary outcomes

Description

Usage

Value

Arguments

Examples