All functions

ML()

ML model

NB-class

NB class object

NB()

Naive Bayes

RATE()

Responder Average Treatment Effect

RATE.surv()

Responder Average Treatment Effect

SL()

SuperLearner wrapper for ml_model

scoring()

Predictive model scoring

aipw()

AIPW estimator

alean()

Assumption Lean inference for generalized linear model parameters

ate()

AIPW (doubly-robust) estimator for Average Treatement Effect

calibration-class

calibration class object

calibration()

Calibration (training)

cate()

Conditional Average Treatment Effect estimation

cate_link()

Conditional Relative Risk estimation

cross_validated-class cross_validated

cross_validated class object

crr()

Conditional Relative Risk estimation

cv()

Cross-validation

design()

Extract design matrix

expand.list()

Create a list from all combination of input variables

ml_model

R6 class for prediction models

nondom()

Find non-dominated points of a set

pava()

Pooled Adjacent Violators Algorithm

predict(<NB>)

Predictions for Naive Bayes Classifier

predict(<density>)

Prediction for kernel density estimates

riskreg()

Risk regression

riskreg_cens()

Binary regression models with right censored outcomes

softmax()

Softmax transformation

solve_ode()

Solve ODE

specify_ode()

Specify Ordinary Differential Equation (ODE)

targeted-class riskreg.targeted ate.targeted

targeted class object