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Calls survAUC::spec.uno().

Assumes random censoring.

times and lp_thresh are arbitrarily set to 0 to prevent crashing, these should be further specified.

Details

All measures implemented from survAUC should be used with care, we are aware of problems in implementation that sometimes cause fatal errors in R. In future updates some of these measures may be re-written and implemented directly in mlr3proba.

Dictionary

This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():

MeasureSurvUnoTNR$new()
mlr_measures$get("surv.uno_tnr")
msr("surv.uno_tnr")

Parameters

IdTypeDefaultRange
timesnumeric-\([0, \infty)\)
lp_threshnumeric0\((-\infty, \infty)\)

Meta Information

  • Type: "surv"

  • Range: \([0, 1]\)

  • Minimize: FALSE

  • Required prediction: lp

Parameter details

  • times (numeric())
    A vector of time-points at which we calculate the TPR/TNR scores.

  • lp_thresh (numeric(1))
    Determines the cutoff threshold of the linear predictor in the calculation of the TPR/TNR scores.

References

Uno H, Cai T, Tian L, Wei LJ (2007). “Evaluating Prediction Rules fort-Year Survivors With Censored Regression Models.” Journal of the American Statistical Association, 102(478), 527–537. doi:10.1198/016214507000000149 .

Super classes

mlr3::Measure -> mlr3proba::MeasureSurv -> mlr3proba::MeasureSurvAUC -> MeasureSurvUnoTNR

Methods

Inherited methods


Method new()

Creates a new instance of this R6 class.

Usage


Method clone()

The objects of this class are cloneable with this method.

Usage

MeasureSurvUnoTNR$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.