DrawCurves_MRMC_pairwise_col: Draw the FROC curves with Colour

Description Usage Arguments

View source: R/DrawCurves.R

Description

Draw an FROC curves and an AFROC curves for user's specified modality and user's specified reader. Using this function repeatedly, we can draw the different reader and modality in a same plane simultaneously. So, we can visualize the difference of modality (reader).

Usage

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DrawCurves_MRMC_pairwise_col(
  StanS4class,
  modalityID,
  readerID,
  type_to_be_passed_into_plot = "p",
  title = TRUE,
  type = 1,
  color_is_changed_by_each_reader = FALSE,
  new.imaging.device = TRUE,
  DrawFROCcurve = TRUE,
  DrawAFROCcurve = FALSE,
  DrawCFPCTP = TRUE,
  Draw.Flexible.upper_y = TRUE,
  Draw.Flexible.lower_y = TRUE,
  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(), ppp() and ... etc

modalityID

This is a vector indicating modalityID whose component is natural namber.

readerID

This is a vector indicating readerID whose component is natural namber.

type_to_be_passed_into_plot

"l" or "p".

title

Logical: TRUE of FALSE. If TRUE (default), then title of curves are drawn.

type

An integer, for the color of background and etc.

color_is_changed_by_each_reader

A logical, if TRUE, then the FROC curves, AFROC curves, and FPF, TPF are colored accordingly by each reader. The aim of FROC analysis is to compare the modality and not reader, so the default value is false, and curves and FPF and TPF are colored by each modalities.

new.imaging.device

Logical: TRUE of FALSE. If TRUE (default), then open a new device to draw curve. Using this we can draw curves in same plain by new.imaging.device=FALSE.

DrawFROCcurve

Logical: TRUE of FALSE. Whether the FROC curve is to be drawn.

DrawAFROCcurve

Logical: TRUE of FALSE. Whether the AFROC curve is to be drawn.

DrawCFPCTP

Logical: TRUE of FALSE. Whether the CFP and CTP points are to be drawn. CFP: Cumulative false positive per lesion (or image) which is also called False Positive Fraction (FPF). CTP Cumulative True Positive per lesion which is also called True Positive Fraction (TPF)..

Draw.Flexible.upper_y

Logical, that is TRUE or FALSE. Whether or not the upper bounds of vertical axis are determined automatically.

Draw.Flexible.lower_y

Logical, that is TRUE or FALSE. Whether or not the lower bounds of vertical axis are determined automatically.

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.


BayesianFROC documentation built on Jan. 13, 2021, 5:22 a.m.