UtilAucBinormal: Binormal model AUC function
In RJafroc: Artificial Intelligence Systems and Observer Performance
UtilAucBinormal R Documentation
Binormal model AUC function
Description
Returns the Binormal model ROC-AUC corresponding to
specified parameters. See also UtilAnalyticalAucsRSM, UtilAucPROPROC
and UtilAucCBM
Usage
UtilAucBinormal(a, b)
Arguments
a
The a parameter of the binormal model (separation of
non-diseased and diseased pdfs)
b
The b parameter of the binormal model (std. dev. of
non-diseased diseased pdf; diseased pdf has unit std. dev)
Value
Binormal model-predicted ROC-AUC
References
Dorfman DD, Alf E (1969) Maximum-Likelihood Estimation of Parameters of Signal-Detection Theory and
Determination of Confidence Intervals - Rating-Method Data, Journal of Mathematical Psychology. 6:487-496.
Examples
a <- 2;b <- 0.7
UtilAucBinormal(a,b)
RJafroc documentation built on Nov. 10, 2022, 5:45 p.m.
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| UtilAucBinormal | R Documentation |
Binormal model AUC function
Description
Returns the Binormal model ROC-AUC corresponding to
specified parameters. See also UtilAnalyticalAucsRSM, UtilAucPROPROC
and UtilAucCBM
Usage
UtilAucBinormal(a, b)
Arguments
a |
The |
b |
The |
Value
Binormal model-predicted ROC-AUC
References
Dorfman DD, Alf E (1969) Maximum-Likelihood Estimation of Parameters of Signal-Detection Theory and Determination of Confidence Intervals - Rating-Method Data, Journal of Mathematical Psychology. 6:487-496.
Examples
a <- 2;b <- 0.7 UtilAucBinormal(a,b)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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