roc_calc: Calculate the ROC curve for a set of observed outcomes and...
In ggmcmc: Tools for Analyzing MCMC Simulations from Bayesian Inference
Description
Usage
Arguments
Value
References
Description
Internal function used by ggs_autocorrelation.
Usage
1
roc_calc(R)
Arguments
R
data frame with the 'value' (predicted probability) and the observed 'Outcome'.
Value
A data frame with the Sensitivity and the Specificity.
References
Fernández-i-Marín, Xavier (2016) ggmcmc: Analysis of MCMC Samples and Bayesian Inference. Journal of Statistical Software, 70(9), 1-20. doi:10.18637/jss.v070.i09
ggmcmc documentation built on Feb. 10, 2021, 5:10 p.m.
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Description Usage Arguments Value References
Description
Internal function used by ggs_autocorrelation.
Usage
1 | roc_calc(R)
|
Arguments
R |
data frame with the 'value' (predicted probability) and the observed 'Outcome'. |
Value
A data frame with the Sensitivity and the Specificity.
References
Fernández-i-Marín, Xavier (2016) ggmcmc: Analysis of MCMC Samples and Bayesian Inference. Journal of Statistical Software, 70(9), 1-20. doi:10.18637/jss.v070.i09
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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