R Graphical Manual

Last data update: 2014.03.03

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R Release (3.2.3)
CranContrib
BioConductor
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Results 1 - 10 of 23 found.
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var.roc (Package: pROC) :

These functions compute the variance of the AUC of a ROC curve.

● Data Source: CranContrib
● Keywords: nonparametric, roc, univar, utilities
● Alias: var, var.auc, var.default, var.roc, var.smooth.roc
● 0 images

ci (Package: pROC) :

This function computes the confidence interval (CI) of a ROC curve. The of argument controls the type of CI that will be computed. By default, the 95% CI are computed with 2000 stratified bootstrap replicates.

● Data Source: CranContrib
● Keywords: nonparametric, roc, univar, utilities
● Alias: ci, ci.default, ci.formula, ci.roc, ci.smooth.roc
● 0 images

power.roc.test (Package: pROC) :

Computes sample size, power, significance level or minimum AUC for ROC curves.

● Data Source: CranContrib
● Keywords: nonparametric, roc, univar, utilities
● Alias: power.roc.test, power.roc.test.list, power.roc.test.numeric, power.roc.test.roc
● 0 images

cov.roc (Package: pROC) :

This function computes the covariance between the AUC of two correlated (or paired) ROC curves.

● Data Source: CranContrib
● Keywords: multivariate, nonparametric, roc, utilities
● Alias: cov, cov.auc, cov.default, cov.roc, cov.smooth.roc
● 0 images

plot.ci (Package: pROC) :

This function adds confidence intervals to a ROC curve plot, either as bars or as a confidence shape.

● Data Source: CranContrib
● Keywords: aplot, hplot, nonparametric, roc, univar, utilities
● Alias: plot.ci, plot.ci.se, plot.ci.sp, plot.ci.thresholds
● 0 images

roc.test (Package: pROC) :

This function compares the AUC or partial AUC of two correlated (or paired) or uncorrelated (unpaired) ROC curves. Several syntaxes are available: two object of class roc (which can be AUC or smoothed ROC), or either three vectors (response, predictor1, predictor2) or a response vector and a matrix or data.frame with two columns (predictors).

● Data Source: CranContrib
● Keywords: htest, multivariate, nonparametric, roc, utilities
● Alias: roc.test, roc.test.auc, roc.test.default, roc.test.formula, roc.test.roc, roc.test.smooth.roc
● 0 images

lines.roc (Package: pROC) :

This convenience function adds a ROC line to a ROC curve.

● Data Source: CranContrib
● Keywords: aplot, hplot, nonparametric, roc, univar, utilities
● Alias: lines.roc, lines.roc.default, lines.roc.formula, lines.roc.roc, lines.roc.smooth.roc, lines.smooth.roc
● 0 images

are.paired (Package: pROC) :

This function determines if two ROC curves can be paired.

● Data Source: CranContrib
● Keywords: logic, programming, roc
● Alias: are.paired, are.paired.auc, are.paired.roc, are.paired.smooth.roc
● 0 images

groupGeneric (Package: pROC) :

Redefine base groupGeneric functions to handle auc and ci objects properly on operations and mathematical operations. Attributes are dropped so that the AUC/CI behaves as a numeric value/matrix, respectively. In the case of AUC, all attributes are dropped, while in CI only the CI-specific attributes are, keeping those necessary for the matrices.

● Data Source: CranContrib
● Keywords: methods
● Alias: Math, Math.auc, Math.ci, Math.ci.auc, Math.ci.coords, Math.ci.se, Math.ci.sp, Ops, Ops.auc, Ops.ci, Ops.ci.auc, Ops.ci.coords, Ops.ci.se, Ops.ci.sp, groupGeneric, groupGeneric.auc, groupGeneric.ci.coords, groupGeneric.ci.se, groupGeneric.ci.sp, groupGeneric.pROC
● 0 images

plot.roc (Package: pROC) :

This function plots a ROC curve. It can accept many arguments to tweak the appearance of the plot. Two syntaxes are possible: one object of class “roc”, or either two vectors (response, predictor) or a formula (response~predictor) as in the roc function.

● Data Source: CranContrib
● Keywords: aplot, hplot, nonparametric, roc, univar, utilities
● Alias: plot.roc, plot.roc.default, plot.roc.formula, plot.roc.roc, plot.roc.smooth.roc, plot.smooth.roc
● 0 images