Package index • RJafroc

All functions
`ChisqrGoodnessOfFit()`	Compute the chisquare goodness of fit statistic for ROC fitting model
`Df2RJafrocDataset()`	Convert ratings arrays to an RJafroc dataset
`DfBinDataset()`	Returns a binned dataset
`DfCreateCorCbmDataset()`	Create paired dataset for testing `FitCorCbm`
`DfExtractCorCbmDataset()`	Extract two arms of a pairing from an MRMC ROC dataset
`DfExtractDataset()`	Extract a subset of treatments and readers from a dataset
`DfFroc2Lroc()`	Simulates an "AUC-equivalent" LROC dataset from an FROC dataset
`DfFroc2Roc()`	Convert an FROC dataset to an ROC dataset
`DfLroc2Froc()`	Simulates an "AUC-equivalent" FROC dataset from an LROC dataset
`DfLroc2Roc()`	Convert an LROC dataset to a ROC dataset
`DfReadDataFile()`	Read a factorial data file
`DfReadXModalities()`	Read a crossed-modality data file
`DfSaveDataFile()`	Save ROC dataset in different formats
`DfWriteExcelDataFile()`	Save dataset object as a JAFROC format Excel file
`FitBinormalRoc()`	Fit the binormal model to selected modality and reader in an ROC dataset
`FitCbmRoc()`	Fit the contaminated binormal model (CBM) to selected modality and reader in an ROC dataset
`FitCorCbm()`	Fit CORCBM to a paired ROC dataset
`FitRsmRoc()`	Fit the radiological search model (RSM) to an ROC dataset
`PlotBinormalFit()`	Plot binormal fit
`PlotCbmFit()`	Plot CBM fitted curve
`PlotEmpOpChrs()`	Plot empirical operating characteristics, ROC, FROC or LROC
`PlotRsmOpChrs()`	RSM predicted operating characteristics, ROC pdfs and AUCs
`RJafroc-package`	Artificial Intelligence Systems and Observer Performance
`RSM_FPF()`	RSM predicted ROC-abscissa as function of z
`RSM_LLF()`	RSM predicted FROC ordinate
`RSM_NLF()`	RSM predicted FROC abscissa
`RSM_TPF()`	RSM predicted ROC-ordinate as function of z
`RSM_pdfD()`	RSM predicted ROC-rating pdf for diseased cases
`RSM_pdfN()`	RSM predicted ROC-rating pdf for non-diseased cases
`RSM_wLLF()`	RSM predicted wAFROC ordinate, cpp code
`SimulateCorCbmDataset()`	Simulate paired binned data for testing FitCorCbm
`SimulateFrocDataset()`	Simulates an MRMC uncorrelated FROC dataset using the RSM
`SimulateFrocFromLrocDataset()`	Simulates an "AUC-equivalent" FROC dataset from an LROC dataset
`SimulateLrocDataset()`	Simulates an uncorrelated LROC dataset using the RSM
`SimulateRocDataset()`	Simulates a binormal model ROC dataset
`SsFrocNhRsmModel()`	Construct RSM NH model for FROC sample size estimation
`SsFrocSampleSize()`	RSM fitted model for FROC sample size
`SsPowerGivenJK()`	Statistical power for specified numbers of readers and cases
`SsPowerGivenJKDbmVarCom()`	Power given J, K and Dorfman-Berbaum-Metz variance components
`SsPowerGivenJKOrVarCom()`	Power given J, K and Obuchowski-Rockette variance components
`SsPowerTable()`	Generate a power table using the OR method
`SsSampleSizeKGivenJ()`	Number of cases, for specified number of readers, to achieve desired power
`St()`	DBM or OR significance testing for a one treatment factorial or two-treatment crossed modality factorial dataset
`StCadVsRad()`	Significance testing: standalone CAD vs. radiologists
`Util2Intrinsic()`	Convert from physical to intrinsic RSM parameters
`Util2Physical()`	Convert from intrinsic to physical RSM parameters
`UtilAnalyticalAucsRSM()`	RSM ROC/AFROC/wAFROC AUC calculator
`UtilAucBIN()`	Binormal model AUC function
`UtilAucCBM()`	CBM AUC function
`UtilAucPROPROC()`	PROPROC AUC function
`UtilDBM2ORVarCom()`	Convert from DBM to OR variance components
`UtilDBMVarComp()`	Utility for Dorfman-Berbaum-Metz variance components
`UtilFigureOfMerit()`	Calculate empirical figures of merit (FOMs) for factorial dataset, standard one-treatment or two-treatment cross-modality
`UtilLesDistr()`	The `lesionID` distribution of a dataset or a supplied 1D-array
`UtilLesWghtsDS()` `UtilLesWghtsLD()`	Lesion weights distribution matrix
`UtilMeanSquares()`	Calculate mean squares for factorial dataset
`UtilOR2DBMVarCom()`	Convert from OR to DBM variance components
`UtilORVarComp()`	Obuchowski-Rockette variance components for dataset
`UtilPseudoValues()`	Pseudovalues for given factorial or crossed modality dataset and FOM
`dataset01`	TONY FROC dataset
`dataset02`	Van Dyke ROC dataset
`dataset03`	Franken ROC dataset
`dataset04`	Federica Zanca FROC dataset
`dataset05`	John Thompson FROC dataset
`dataset06`	Magnus FROC dataset
`dataset07`	Lucy Warren FROC dataset
`dataset08`	Monica Penedo ROC dataset
`dataset09`	Nico Karssemeijer ROC dataset (CAD vs. radiologists)
`dataset10`	Mark Ruschin ROC dataset
`dataset11`	Dobbins 1 FROC dataset
`dataset12`	Dobbins 2 ROC dataset
`dataset13`	Dobbins 3 FROC dataset
`dataset14`	Federica Zanca real (as opposed to inferred) ROC dataset
`datasetBinned123`	Binned dataset suitable for checking `FitCorCbm`; seed = 123
`datasetBinned124`	Binned dataset suitable for checking `FitCorCbm`; seed = 124
`datasetBinned125`	Binned dataset suitable for checking `FitCorCbm`; seed = 125
`datasetCadLroc`	Nico Karssemeijer LROC dataset (CAD vs. radiologists)
`datasetCadSimuFroc`	Simulated FROC CAD vs. RAD dataset
`datasetDegenerate`	Simulated degenerate ROC dataset (for testing purposes)
`datasetROI`	Simulated ROI dataset
`datasetX`	John Thompson crossed modality FROC dataset
`isBinnedDataset()`	Determine if a dataset is binned
`isValidDataset()`	Check the validity of a dataset for FOM and other input parameters

Reference

All functions