sortAUC: Prints a Ranking for AUCs for MRMC Data
In BayesianFROC: FROC Analysis by Bayesian Approaches

Description Usage Arguments Details Value Examples

prints a modality ranking according to their AUCs.

1	sortAUC(StanS4class, digits = 3, simple = FALSE)

StanS4class

An S4 object of class stanfitExtended which is an inherited class from the S4 class stanfit. This R object is a fitted model object as a return value of the function fit_Bayesian_FROC().

To be passed to DrawCurves() ... etc

digits

To be passed to round() for AUC, to determine the significant digits of AUCs.

simple

Logical, TRUE or FALSE. If TRUE, then it is simple.

@export

This is a ranking. Sort a data-frame involving AUC and corresponding modality IDs.

A data-frame, representing sorted ranking of modality ID and its AUC. Revised 2019 Sept 9

 ## Not run: 
#========================================================================================
#            1)      Fit a model to an MRMC data-set named dd
#========================================================================================

                    fit <- fit_Bayesian_FROC(
                                                ite  = 1111,
                                             summary = FALSE,
                                                 cha = 1,
                                            dataList = dd
                                             )



#========================================================================================
#            2)         Sort the AUC and make a ranking table
#========================================================================================



                              sortAUC(fit)



# Then, a ranking table will appear.

                                                               # Reviesed 2019 Sept 9

 
## End(Not run)