Targeted Inference

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Documentation for package ‘targeted’ version 0.5

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Code demos. Use demo() to run them.
• Package NEWS.

Help Pages

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