aipw |
AIPW estimator |
alean |
Assumption Lean inference for generalized linear model parameters |
ate |
AIPW (doubly-robust) estimator for Average Treatement Effect |
ate.targeted |
targeted class object |
calibrate |
Calibration (training) |
calibration |
Calibration (training) |
calibration-class |
calibration class object |
cate |
Conditional Average Treatment Effect estimation |
cate_link |
Conditional Relative Risk estimation |
cross_validated |
cross_validated class object |
cross_validated-class |
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 |
isoreg |
Pooled Adjacent Violators Algorithm |
isoregw |
Pooled Adjacent Violators Algorithm |
ML |
ML model |
ml_model |
R6 class for prediction models |
NB |
Naive Bayes |
NB-class |
NB class object |
NB2 |
Naive Bayes |
nondom |
Find non-dominated points of a set |
pava |
Pooled Adjacent Violators Algorithm |
predict.density |
Prediction for kernel density estimates |
predict.NB |
Predictions for Naive Bayes Classifier |
RATE |
Responder Average Treatment Effect |
RATE.surv |
Responder Average Treatment Effect |
riskreg |
Risk regression |
riskreg.targeted |
targeted class object |
riskreg_cens |
Binary regression models with right censored outcomes |
riskreg_fit |
Risk regression |
riskreg_mle |
Risk regression |
scoring |
Predictive model scoring |
SL |
SuperLearner wrapper for ml_model |
softmax |
Softmax transformation |
solve_ode |
Solve ODE |
specify_ode |
Specify Ordinary Differential Equation (ODE) |
targeted-class |
targeted class object |