roc_calc

data frame with the 'value' (predicted probability) and the observed 'Outcome'.

Internal function used by <code><a rd-options="" href="/link/ggs_autocorrelation?package=ggmcmc&version=1.5.1.1" data-mini-rdoc="ggmcmc::ggs_autocorrelation">ggs_autocorrelation</a></code>.

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
(Fern<c3><a1>ndez-i-Mar<c3><ad>n, 2016 <doi:10.18637/jss.v070.i09>).

Xavier i Marín

ggmcmc

Tools for Analyzing MCMC Simulations from Bayesian Inference

Xavier Fern<c3><a1>ndez i Mar<c3><ad>n

roc_calc function

Internal function used by <code><a rd-options='' href='ggs_autocorrelation'>ggs_autocorrelation</a></code>.

roc_calc: Calculate the ROC curve for a set of observed outcomes and predicted probabilities

Description

Usage

Arguments

Value

References