# ROC curve estimator based on kernel estimates of the constituent distributions

**Rufibach, K.** (2011).

Code to compute the kernel density estimate of the ROC curve and the corresponding AUC proposed in Hall & Hyndman (2003). This code was used to compare the log-concave ROC curve estimate to this kernel based estimate in Rufibach (2012).

This code contains a small example using data available in logcondens.
The methodology is also available in the function smooth() in the R package pROC .

# References

Hall, P.G., Hyndman, R.J. (2003). *Improved methods for bandwidth selection when estimating ROC curves*, Statist. Probab. Lett. 64, 181-189. doi

**Rufibach, K.** (2012). *A smooth ROC curve estimator based on log-concave density estimates.* Int. J. Biostat., accepted. arxiv