Implements a very fast C++ algorithm to quickly bootstrap
receiver operating characteristics (ROC) curves and derived performance metrics, including the area under the
curve (AUC) as well as the true and false positive rate. The analysis of paired
receiver operating curves is supported as well, so that a comparison of two predictors is possible.
You can also plot the results and calculate confidence intervals.
Currently the calculation of 100000 bootstrap replicates for 500 observations
takes about one second.
R (>= 3.2.2), ggplot2, methods, stats, utils

R (>= 3.2.0), ggplot2, methods, stats, utils

Implements a very fast C++ algorithm to quickly bootstrap receiver
operating characteristics (ROC) curves and derived performance metrics,
including the area under the curve (AUC) and the partial area under the curve as well as
the true and false positive rate. The analysis of paired receiver operating curves is supported as well,
so that a comparison of two predictors is possible. You can also plot the
results and calculate confidence intervals. On a typical desktop computer the time needed for
the calculation of 100000 bootstrap replicates given 500 observations requires time on the
order of magnitude of one second.

The Full Bayesian Significance Test and the e-Value
Provides access to a range of functions for computing and visualising the Full Bayesian Significance Test (FBST) and the e-value for testing a sharp hypothesis against its alternative. The methods are widely applicable as long as a posterior MCMC sample is available. For details on the computation and theory of the FBST see <arXiv:2005.13181>.

The Full Bayesian Evidence Test, Full Bayesian Significance Test
and the e-value
Provides access to a range of functions for computing and visualizing the Full Bayesian Significance Test (FBST) and the e-value for testing a sharp hypothesis against its alternative, and the Full Bayesian Evidence Test (FBET) and the (generalized) Bayesian evidence value for testing a composite (or interval) hypothesis against its alternative. The methods are widely applicable as long as a posterior MCMC sample is available. For details on the computation and theory of the FBST see <arXiv:2005.13181>.