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Estimate significance of AUC by permutation test.
permTestAUC( d, modelName, yName, yTarget = TRUE, ..., na.rm = FALSE, returnScores = FALSE, nrep = 100, parallelCluster = NULL )
AUC statistic
data.frame
character model column name
character outcome column name
target to match to y
extra arguments (not used)
logical, if TRUE remove NA values
logical if TRUE return detailed permutedScores
number of permutation repetitions to estimate p values.
(optional) a cluster object created by package parallel or package snow
set.seed(25325) d <- data.frame(x1=c(1,2,3,4,5,6,7,7), y=c(FALSE,TRUE,FALSE,FALSE, TRUE,TRUE,FALSE,TRUE)) permTestAUC(d,'x1','y',TRUE)
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