summary_EAP_CI_srsc: Summary

In BayesianFROC: FROC Analysis by Bayesian Approaches

Description

EAP and CI

Usage

summary_EAP_CI_srsc(StanS4class, dig = 5, summary = TRUE)

Arguments

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
dig	digits of estimates.
summary	Logical: TRUE of FALSE. Whether to print the verbose summary. If TRUE then verbose summary is printed in the R console. If FALSE, the output is minimal. I regret, this variable name should be verbose.

Value

The estimates

Examples

## Not run: 
#================The first example=======================================================


#1) Build the data for singler reader and single modality  case.

dat <- list(c=c(3,2,1),    #Confidence level
            h=c(97,32,31), #Number of hits for each confidence level
            f=c(1,14,74),  #Number of false alarms for each confidence level

            NL=259,       #Number of lesions
            NI=57,        #Number of images
            C=3)          #Number of confidence level

# where, c denotes Confidence level,
#        h denotes number of Hits for each confidence level,
#        f denotes number of False alarms for each confidence level,
#        NL denotes Number of Lesions,
#        NI denotes Number of Images,


#   2) Fit the FROC model to the above data

          fit <-   BayesianFROC::fit_Bayesian_FROC(dat)

#   3) Extract estimates, that is posterior means and 95% credible intervals


        estimates <- summary_EAP_CI_srsc(  fit )



## End(Not run)# dottest

BayesianFROC documentation built on Jan. 23, 2022, 9:06 a.m.