mlr3proba 0.2.0

MeasureSurvCindex added. Generalises all c-index measures with a fast C++ implementation
Akritas estimator added to mlr3learners.proba repo
Added scoring rule MeasureSurvSchmid
Addd calibration measures MeasureSurvCalibrationBeta and MeasureSurvCalibrationAlpha
surv.brier alias added for surv.graf
response parameter added to PipeOpCrankCompositor and crankcompositor to now optionally fill response predict type with same values as crank
Added PipeOpProbregrCompostior and compose_probregr for composition to distr return type from (a) regression learner(s) predicting response and se
Added PipeOpSurvAvg and surv_averager pipeline for weighted model averaging of distr, lp, crank, and response predictions.

The following measures are deprecated use MeasureSurvCindex instead with following parameters: MeasureSurvBeggC, use defaults; MeasureSurvHarrellC, use defaults; MeasureSurvUnoC, use weight_meth = 'G/2'; MeasureSurvGonenC, use weight_method = 'GH'
MeasureSurvGrafSE, MeasureSurvLoglossSE, MeasureSurvIntLoglossSE, MeasureSurvRMSESE, MeasureSurvMSESE, and MeasureSurvMAESE all deprecated and will be deleted in v0.4.0. Use msr("surv.graf", se = TRUE) instead (for example).
Measures renamed such that surv.nagelkR2 is now surv.nagelk_r2, analogously for all R2, AUC, TPR, and TNR measures. Old constructors will be deleted in v0.4.0.
Renamed distrcompose and crankcompose to distr_compose and crank_compose. Old ids will be deleted in v0.4.0.

Measures renamed such that surv.nagelkR2 is now surv.nagelk_r2, analogously for all R2, AUC, TPR, and TNR measures. Old constructors will be deleted in v0.4.0.
MeasureSurvGraf and MeasureSurvIntLogloss now have much faster C++ implementation

LearnerSurvGlmnet, LearnerSurvCVGlmnet, LearnerSurvXgboost and LearnerSurvRanger have been moved to the mlr3learners repo
LearnerSurvGBM has been moved to https://www.github.com/mlr3learners/mlr3learners.gbm
LearnerSurvMboost, LearnerSurvGlmBoost, LearnerSurvGamboost, LearnerSurvBlackboost have been moved to https://www.github.com/mlr3learners/mlr3learners.mboost

mlr3proba 0.1.6

Early release due to backward compatibility error introduced by an upstream dependency
Minor updates to mboost family of learners: added gehan family, fixed parameters for cindex, added support for: weights, response predict type, importance, selected_features
Minor internal changes
All density learners except LearnerDensHist and LearnerDensKDE have been moved to the mlr3learners org
The following survival learners have been moved to the mlr3learners org, LearnerSurv: Flexible, ObliqueRSF, Penalized, RandomForestSRC
Bugfix in LearnerSurvXgboost previously lp was erroneously returned as exp(lp)
Now licenced under LPGL-3

LearnerSurvParametric and LearnerSurvNelson moved to mlr3learners/mlr3learners.survival repo
LearnerSurvCoxboost and LearnerSurvCVCoxboost moved to mlr3learners/mlr3learners.coxboost repo
LearnerSurvSVM moved to mlr3learners/mlr3learners.survivalsvm repo
In the next release, all learners except for LearnerSurvKaplan, LearnerSurvCoxPH, and LearnerDensHist will be moved to the mlr3learners org
Minor internal changes

Density estimation has now been added to mlr3proba, see TaskDens, LearnerDens, PredictionDens, and MeasureDens.
Added mlr_tasks_faithful and mlr_tasks_precip for density task examples
Added mlr_task_generators_simdens for generating density tasks
Added learners for density estimation, see mlr3::mlr_learners$keys("^dens") for the full list
In line with mlr3 0.1.7, public methods train_internal, predict_internal, score_internal are now private methods .train,.predict,.score
Converted to roxygen2 R6 documentation

Changed lp in surv.parametric to include the intercept, which is in line with survival::survreg. Now exp(pred$lp) is equal to the predicted survival time for AFTs
Moved mboost to suggests
Added response predict type, which predicts the time until event. Currently only supported for AFT models in surv.parametric
Added measures for response predict type: MeasureSurvMAE, MeasureSurvMAESE, MeasureSurvMSE, MeasureSurvMSESE, MeasureSurvRMSE, MeasureSurvRMSESE

Added method argument to integrated scores and added weighting by bin-width
Added notes to IGS documentation regarding default methods and comparison to other packages
Added method to MeasureSurvIntegrated constructor and fields
Fixed mistake in documentation of: TaskSurv, MeasureSurvUnoC
Added missing LearnerSurvRpart parameter parms and cost
Fixed errors in r-patched-solaris and r-devel debian-clang