Calls survAUC::sens.uno().
Assumes random censoring.
times and lp_thresh are arbitrarily set to 0 to prevent crashing, these should be further
specified.
This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():
MeasureSurvUnoTPR$new()
mlr_measures$get("surv.uno_tpr")
msr("surv.uno_tpr")
Type: "surv"
Range: \([0, 1]\)
Minimize: FALSE
Required prediction: lp
mlr3::Measure -> mlr3proba::MeasureSurv -> mlr3proba::MeasureSurvIntegrated -> mlr3proba::MeasureSurvAUC -> MeasureSurvUnoTPR
lp_threshnumeric(1)
Threshold for linear predictor when calculating TPR/TNR.
new()Creates a new instance of this R6 class.
MeasureSurvUnoTPR$new(times = 0, lp_thresh = 0)
times(numeric())
If integrate == TRUE then a vector of time-points over which to integrate the score.
If integrate == FALSE then a single time point at which to return the score.
lp_threshnumeric(1)
Determines where to threshold the linear predictor for calculating the TPR/TNR.
clone()The objects of this class are cloneable with this method.
MeasureSurvUnoTPR$clone(deep = FALSE)
deepWhether to make a deep clone.
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 these
measures will all be re-written and implemented directly in mlr3proba.
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. 10.1198/016214507000000149.
Other survival measures:
mlr_measures_surv.beggC,
mlr_measures_surv.calib_alpha,
mlr_measures_surv.calib_beta,
mlr_measures_surv.chambless_auc,
mlr_measures_surv.cindex,
mlr_measures_surv.gonenC,
mlr_measures_surv.grafSE,
mlr_measures_surv.graf,
mlr_measures_surv.harrellC,
mlr_measures_surv.hung_auc,
mlr_measures_surv.intloglossSE,
mlr_measures_surv.intlogloss,
mlr_measures_surv.logloss_se,
mlr_measures_surv.logloss,
mlr_measures_surv.maeSE,
mlr_measures_surv.mae,
mlr_measures_surv.mseSE,
mlr_measures_surv.mse,
mlr_measures_surv.nagelk_r2,
mlr_measures_surv.oquigley_r2,
mlr_measures_surv.rmseSE,
mlr_measures_surv.rmse,
mlr_measures_surv.schmid,
mlr_measures_surv.song_auc,
mlr_measures_surv.song_tnr,
mlr_measures_surv.song_tpr,
mlr_measures_surv.unoC,
mlr_measures_surv.uno_auc,
mlr_measures_surv.uno_tnr,
mlr_measures_surv.xu_r2
Other AUC survival measures:
mlr_measures_surv.chambless_auc,
mlr_measures_surv.hung_auc,
mlr_measures_surv.song_auc,
mlr_measures_surv.song_tnr,
mlr_measures_surv.song_tpr,
mlr_measures_surv.uno_auc,
mlr_measures_surv.uno_tnr
Other lp survival measures:
mlr_measures_surv.beggC,
mlr_measures_surv.calib_beta,
mlr_measures_surv.chambless_auc,
mlr_measures_surv.gonenC,
mlr_measures_surv.hung_auc,
mlr_measures_surv.nagelk_r2,
mlr_measures_surv.oquigley_r2,
mlr_measures_surv.song_auc,
mlr_measures_surv.song_tnr,
mlr_measures_surv.song_tpr,
mlr_measures_surv.uno_auc,
mlr_measures_surv.uno_tnr,
mlr_measures_surv.xu_r2