View source: R/DfCreateCorCbmDataset.R
DfCreateCorCbmDataset | R Documentation |
FitCorCbm
The paired dataset is generated using bivariate sampling; details are in referenced publication
DfCreateCorCbmDataset( seed = 123, K1 = 50, K2 = 50, desiredNumBins = 5, muX = 1.5, muY = 3, alphaX = 0.4, alphaY = 0.7, rhoNor = 0.3, rhoAbn2 = 0.8 )
seed |
The seed variable, default is 123; set to NULL for truly random seed |
K1 |
The number of non-diseased cases, default is 50 |
K2 |
The number of diseased cases, default is 50 |
desiredNumBins |
The desired number of bins; default is 5 |
muX |
The CBM μ parameter in condition X |
muY |
The CBM μ parameter in condition Y |
alphaX |
The CBM α parameter in condition X |
alphaY |
The CBM alpha parameter in condition Y |
rhoNor |
The correlation of non-diseased case z-samples |
rhoAbn2 |
The correlation of diseased case z-samples, when disease is visible in both conditions |
The ROC data is bined to 5 bins in each condition.
The return value is the desired dataset, suitable for testing FitCorCbm
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Zhai X, Chakraborty DP (2017) A bivariate contaminated binormal model for robust fitting of proper ROC curves to a pair of correlated, possibly degenerate, ROC datasets. Medical Physics. 44(6):2207–2222.
## seed <- 1 ## this gives unequal numbers of bins in X and Y conditions for 50/50 dataset dataset <- DfCreateCorCbmDataset() ## this takes very long time!! used to show asymptotic convergence of ML estimates ## dataset <- DfCreateCorCbmDataset(K1 = 5000, K2 = 5000)
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