Man pages for BuyseTest
Generalized Pairwise Comparisons

as.data.table.performanceConvert Performance Objet to data.table
aucEstimation of the Area Under the ROC Curve (EXPERIMENTAL)
autoplot.sensitivityGraphical Display for Sensitivity Analysis
boot2pvalueCompute the p.value from the distribution under H1
BuyseMultCompAdjustment for Multiple Comparisons
BuyseTestGeneralized Pairwise Comparisons (GPC)
BuyseTest.optionsGlobal options for BuyseTest package
BuyseTest.options-classClass "BuyseTest.options" (global setting for the BuyseTest...
BuyseTest.options-methodsMethods for the class "BuyseTest.options"
BuyseTest-packageBuyseTest package: Generalized Pairwise Comparisons
BuyseTTEMTime to Event Model
calcIntegralSurv2_cppC++ Function pre-computing the Integral Terms for the Peron...
coef.BuyseTestAucExtract the AUC Value
coef.BuyseTestBrierExtract the Brier Score
confint.BuyseTestAucExtract the AUC value with its Confidence Interval
confint.BuyseTestBrierExtract the Brier Score with its Confidence Interval
constStrataStrata creation
discreteRootDichotomic search for monotone function
dot-calcIntegralCif_cppC++ Function Computing the Integral Terms for the Peron...
dot-calcIntegralSurv_cppC++ Function Computing the Integral Terms for the Peron...
dot-colCenter_cppSubstract a vector of values in each column
dot-colCumSum_cppColumn-wise cumulative sum
dot-colMultiply_cppMultiply by a vector of values in each column
dot-colScale_cppDivide by a vector of values in each column
dot-information.logitInformation for Logistic Regressions
dot-rowCenter_cppSubstract a vector of values in each row
dot-rowCumProd_cppApply cumprod in each row
dot-rowCumSum_cppRow-wise cumulative sum
dot-rowMultiply_cppMultiply by a vector of values in each row
dot-rowScale_cppDividy by a vector of values in each row
dot-score.logitScore for Logistic Regressions
dot-vcov.logitVariance-covariance matrix for Logistic Regressions
GPC_cppC++ function performing the pairwise comparison over several...
iid.BuyseTestAucExtract the idd Decomposition for the AUC
iid.BuyseTestBrierExtract the idd Decomposition for the Brier Score
iid.prodlimExtract i.i.d. decomposition from a prodlim model
internal-initializationinternal functions for BuyseTest - initialization
internal-printinternal functions for BuyseTest - display
performanceAssess Performance of a Classifier
performanceResampleUncertainty About Performance of a Classifier (EXPERIMENTAL)
pnormexpCumulative Distribution Function of a Gaussian Variable Plus...
pnormweibullCumulative Distribution Function of a Gaussian Variable Plus...
powerBuyseTestPerforming simulation studies with BuyseTest
predict.BuyseTTEMPrediction with Time to Event Model
predict.logitPredicted Probability with Influence Function
qnormexpDensity of a Gaussian Variable Plus an Exponential Variable
qnormweibullDensity of a Gaussian Variable Plus an Weibull Variable
rbind.performanceCombine Resampling Results For Performance Objects
S4BuysePower-classClass "S4BuysePower" (output of BuyseTest)
S4BuysePower-showShow Method for Class "S4BuysePower"
S4BuysePower-summarySummary Method for Class "S4BuysePower"
S4BuyseTest-classClass "S4BuyseTest" (output of BuyseTest)
S4BuyseTest-coefCoef Method for Class "S4BuyseTest"
S4BuyseTest-confintConfidence Intervals for Model Parameters
S4BuyseTest-getCountExtract the Number of Favorable, Unfavorable, Neutral,...
S4BuyseTest-getIidExtract the H-decomposition of the Estimator
S4BuyseTest-getPairScoreExtract the Score of Each Pair
S4BuyseTest-getPseudovalueExtract the pseudovalues of the Estimator
S4BuyseTest-getSurvivalExtract the Survival and Survival Jumps
S4BuyseTest-sensitivitySensitivity Analysis for the Choice of the Thresholds
S4BuyseTest-showShow Method for Class "S4BuyseTest"
S4BuyseTest-summarySummary Method for Class "S4BuyseTest"
simCompetingRisksSimulation of Gompertz competing risks data for the BuyseTest
simulationSimulation of data for the BuyseTest
summary.performanceSummary Method for Performance Objects
testArgsCheck Arguments Passed to BuyseTest
validFCTsCheck Arguments of a function.
BuyseTest documentation built on March 31, 2023, 6:55 p.m.