pROC is a set of tools to visualize, smooth and compare receiver operating characteristic (ROC curves). (Partial) area under the curve (AUC) can be compared with statistical tests based on U-statistics or bootstrap. Confidence intervals can be computed for (p)AUC or ROC curves.

More screenshots and examples…

If you use pROC in published research, please cite the following paper:

Xavier Robin, Natacha Turck, Alexandre Hainard, Natalia Tiberti, Frédérique Lisacek, Jean-Charles Sanchez and Markus Müller (2011). pROC: an open-source package for R and S+ to analyze and compare ROC curves. *BMC Bioinformatics*, **12**, p. 77. DOI: 10.1186/1471-2105-12-77.

- Authors
- Xavier Robin, Natacha Turck, Alexandre Hainard, Natalia Tiberti, Frédérique Lisacek, Jean-Charles Sanchez and Markus Müller
- Contact
- Xavier Robin
- License
- GPLv3

pROC comes in two flavours: a command line version for the R statistical software environment, and a graphical user interface (GUI) for S+.

## R |
## S+ |
---|---|

This version is intended to be employed through the R command line. - Version: 1.5.3 (released on August 31st, 2012)
- Download pROC from CRAN
- Download R
- Follow pROC's development on GitHub
- Direct downloads:
## InstallationThere is no need to download the package. The installation can be done in one command directly from R: install.packages("pROC") The package must then be loaded with: library(pROC) To get help, enter the following in the R prompt: ?pROC ## UpdateAny of the following commands will update pROC if possible: install.packages("pROC") update.packages() # will install updates to all your packages |
This version is intended to be employed with the TIBCO Spotfire S+ program. It has a graphical user interface (GUI), but the command line is also available. - Version: 1.4.4 (released on August 10th, 2011)
- Download from CSAN
- Get Spotfire S+ from TIBCO (proprietary)
- Direct downloads:
## InstallationIn the S+ command prompt (in Windows, you can open it from S+ install.pkgutils() Then open the After loading from the library(pROC) More details about installation… ## UpdateOpen the You can also repeat the installation to get the latest version of pROC, or type in the command line: update.packages() |

- 1.5.3 (2011-08-31) (R, release notes)
- AUC specification was lost when
`roc.test`

,`cov`

or`var`

was passed an`auc`

' object. - Correct computation of "accuracy" in
`coords`

(thanks to Kosuke Yoshihara for the report). - 1.5.1 (2011-03-09) (R, release notes)
- Faster loading of the package (thanks to Prof Brian Ripley and Glenn Lawyer for the report).
- 1.5 (2011-12-12) (R, release notes)
- New
`cov`

and`var`

functions. `coords`

accepts new`ret`

values: "accuracy", "tn", "tp", "fn", "fp", "npv", "ppv", "1-specificity", "1-sensitivity", "1-npv", "1-ppv", "npe" and "ppe".- New
`legacy.axes`

argument to`plot`

1-specificity rather than specificity. - New
`axes`

argument to turn off the plotting of the axis. - New
`logcondens`

and`logcondens.smooth`

(Univariate Log-Concave Density Estimation) smoothing methods. - New function
`has.partial.auc`

to determine if an AUC is full or partial. - New argument
`drop`

for`coords`

. `auc`

and`multiclass.auc`

objects now also have secondary class`numeric`

.- Updated load call.
- Delong's CI reversed in ROC curves with
`direction=">"`

. - Delong's CI AUC returned values > 1 or < 0 in some rare cases.
- Minor improvements in documentation.
- 1.4.4 (2011-08-10) (R, S+, release notes)
- Fixed alternative for one-tailed tests.
- Removed COPYING file to fix a warning in r-devel.
- 1.4.3 (2011-03-18) (R, S+, release notes)
- Updated citation.
- 1.4.2 (2011-03-03) (R, S+, release notes)
- Fixed bootstrap
`roc.test`

generating NAs when`smooth.roc`

s were used with`reuse.auc=FALSE`

(thanks to Buddy for the report). - Documented a warning that was missing in
`roc.test`

. - Updated citation.
- 1.4.1 (2011-01-27) (R, S+, release notes)
- Venkatraman's test for unpaired ROC curves.
- 1.4 (2011-01-21) (R, S+, release notes)
- 'smooth' does not apply on
`ordered`

factors anymore. - Multi-class AUC support (R only).
- Can choose how
`best`

thresold is determined (`best.method`

and`best.weights`

in`coords`

and`print.thres.best.method`

and`print.thres.best.weights`

in`plot.roc`

). - Minor fixes in documentation (R and S+) and
`citation`

(S+ only). `print`

now prints the response instead of*response*and more informative data in`htest`

s.- Bootstrap with
`ci.auc`

consumes much less memory. - Unpaired bootstrap and DeLong's test.
- Specificity and sensitivity tests (in
`roc.test`

). - 1.3.2 (2010-08-24) (R, S+, release notes)
`print.auc`

printed incorrect CI in`plot.roc`

(thanks to Alexander B. Leichtle for the report).- Failed to detect local maximas in
`coords`

when 2 or less points were selected. - Don't consider ROC extremities (+-Inf at 1.0/0.0 SE<->SP) as local maximas.
- 1.3.1 (2010-08-18) (R, release notes)
- Sensitivity and specificity were inverted in coords when results were reported as list.
- Faster checks with
`\dontrun{}`

in`roc.test`

. - 1.3 (2010-08-13) (R, S+, release notes)
- CI is not re-computed by default in
`smooth.roc`

. You can still turn it on with`reuse.ci=TRUE`

. - New function
`are.paired`

. - Local maximas could be incorrectly detected in
`coords`

(and`plot.roc`

) with`predictor`

s containing more than 2 levels. - New method
`venkatraman`

for`roc.test`

. - MASS and tcltk packages are now only suggested instead of required (R only).
`...`

not passed correctly in`plot.ci.se`

with`type="bars"`

resulting in an error (R only).- 1.2.1 (2010-05-11) (R, S+, release notes)
- Handle
`method`

arguments for`smooth.roc`

and`ci.auc`

separately in`roc.default`

(R-only). - Added
`auc.polygon.*`

and`max.auc.polygon.*`

arguments for`polygon`

in`plot.roc`

. - 1.2 (2010-05-09) (R, release notes)
- Added DeLong method in
`ci.auc`

(with a GUI, S+ only). - Return value of ci.auc does not contain an
`"aucs"`

item anymore. - Put most examples with bootstrap within
`\dontrun{}`

blocks for faster (but less useful) checks execution. - 1.1 (2010-05-05) (R, S+, release notes)
- Added
`lines.roc`

functions for ROC. - Added
`type`

argument for both`lines.roc`

and`plot.roc`

. - Added
`print.auc.col`

argument to`plot.roc`

. - Fixed a warning in
`roc.test.default`

when the class of`predictor1`

had several elements. - Fixed an encoding failure during the checks on MacOS X (R only).
- 1.0.1 (2010-04-28) (R, release notes)
- Reduced examples execution time. Added low
`boot.n`

in the slowest examples and`reuse.auc`

and`reuse.ci`

arguments in`smooth.roc.roc`

. - 1.0 (2010-04-27) (R, S+, release notes)
- First public release.

Please report any bug you may encounter to Xavier Robin.

- James Carpenter and John Bithell (2000) “Bootstrap condence intervals: when, which, what? A practical guide for medical statisticians”.
*Statistics in Medicine***19**, 1141–1164. DOI: 10.1002/(SICI)1097-0258(20000515)19:9<1141::AID-SIM479>3.0.CO;2-F; PMID: 10797513. - Elisabeth R. DeLong, David M. DeLong and Daniel L. Clarke-Pearson (1988) “Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach”.
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*Journal of Statistical Software*,**39**, 1–28. URL: jstatsoft.org/v39/i06. - Tom Fawcett (2006) “An introduction to ROC analysis”.
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*The Stata journal***9**, 1. PMID: 20161343. - Xavier Robin, Natacha Turck
*et al.*(2011) “pROC: an open-source package for R and S+ to analyze and compare ROC curves”.*BMC Bioinformatics*,**12**, 77. DOI: 10.1186/1471-2105-12-77. - E. S. Venkatraman and Colin B. Begg (1996) “A distribution-free procedure for comparing receiver operating characteristic curves from a paired experiment”.
*Biometrika***83**, 835–848. DOI: 10.1093/biomet/83.4.835 - E. S. Venkatraman (2000) “A Permutation Test to Compare Receiver Operating Characteristic Curves”.
*Biometrics***56**, 1134–1138. DOI: 10.1111/j.0006-341X.2000.01134.x. - Kelly H. Zou, W. J. Hall and David E. Shapiro (1997) “Smooth non-parametric receiver operating characteristic (ROC) curves for continuous diagnostic tests”.
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