Calculates the standard error of MeasureSurvIntLogloss.

If integrated == FALSE then the standard error of the loss, L, is approximated via, $$se(L) = sd(L)/\sqrt{N}$$ where $$N$$ are the number of observations in the test set, and $$sd$$ is the standard deviation.

If integrated == TRUE then correlations between time-points need to be taken into account, therefore $$se(L) = \sqrt{\frac{\sum_{i = 1}^M\sum_{j=1}^M \Sigma_{i,j}}{NT^2}}$$ where $$\Sigma_{i, j}$$ is the sample covariance matrix over $$M$$ distinct time-points.

## Format

R6::R6Class() inheriting from MeasureSurvIntegrated/MeasureSurv.

## Construction

MeasureSurvIntLoglossSE$new(integrated = TRUE, times, eps = 1e-15) mlr_measures$get("surv.intloglossSE")
msr("surv.intloglossSE")

• integrated :: logical(1)
If TRUE (default), returns the integrated score; otherwise, not integrated.

• times :: vector()
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.

• eps :: numeric(1)
Very small number to set zero-valued predicted probabilities to, in order to prevent errors in log(0) calculation.

## Meta Information

• Type: "surv"

• Range: $$[0, \infty)$$

• Minimize: TRUE

• Required prediction: distr

## Fields

See MeasureSurv, as well as all variables passed to the constructor.

As well as

• eps :: numeric(1)
Very small number to set zero-valued predicted probabilities to, in order to prevent errors in log(0) calculation.

Graf E, Schmoor C, Sauerbrei W, Schumacher M (1999). “Assessment and comparison of prognostic classification schemes for survival data.” Statistics in Medicine, 18(17-18), 2529--2545. doi: 10.1002/(sici)1097-0258(19990915/30)18:17/18<2529::aid-sim274>3.0.co;2-5 .

Other survival measures: MeasureSurvBeggC, MeasureSurvChamblessAUC, MeasureSurvGonenC, MeasureSurvGrafSE, MeasureSurvGraf, MeasureSurvHarrellC, MeasureSurvHungAUC, MeasureSurvIntLogloss, MeasureSurvLoglossSE, MeasureSurvLogloss, MeasureSurvMAESE, MeasureSurvMAE, MeasureSurvMSESE, MeasureSurvMSE, MeasureSurvNagelkR2, MeasureSurvOQuigleyR2, MeasureSurvRMSESE, MeasureSurvRMSE, MeasureSurvSongAUC, MeasureSurvSongTNR, MeasureSurvSongTPR, MeasureSurvUnoAUC, MeasureSurvUnoC, MeasureSurvUnoTNR, MeasureSurvUnoTPR, MeasureSurvXuR2
Other Probabilistic survival measures: MeasureSurvGrafSE, MeasureSurvGraf, MeasureSurvIntLogloss, MeasureSurvLoglossSE, MeasureSurvLogloss
Other distr survival measures: MeasureSurvGrafSE, MeasureSurvGraf, MeasureSurvIntLogloss, MeasureSurvLoglossSE, MeasureSurvLogloss