Generic Machine Learning Inference

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Documentation for package ‘GenericML’ version 0.2.2

• DESCRIPTION file.
• Package NEWS.

Help Pages

BLP	Performs BLP regression
CLAN	Performs CLAN
GATES	Performs GATES regression
GenericML	Generic Machine Learning Inference
GenericML_combine	Combine several GenericML objects
GenericML_single	Single iteration of the GenericML algorithm
get_best	Accessor function for the best learner estimates
get_BLP	Accessor function for the BLP generic target estimates
get_CLAN	Accessor function for the CLAN generic target estimates
get_GATES	Accessor function for the GATES generic target estimates
heterogeneity_CLAN	Evaluate treatment effect heterogeneity along CLAN variables
lambda_parameters	Estimate the two lambda parameters
Med	Calculate lower and upper median
plot.GenericML	Plot method for a '"GenericML"' object
print.BLP_info	Print method for a '"BLP_info"' object
print.CLAN_info	Print method for a '"CLAN_info"' object
print.GATES_info	Print method for a '"GATES_info"' object
print.GenericML	Print method for a 'GenericML' object
print.heterogeneity_CLAN	Print method for a '"heterogeneity_CLAN"' object
propensity_score	Propensity score estimation
proxy_BCA	Baseline Conditional Average
proxy_CATE	Conditional Average Treatment Effect
quantile_group	Partition a vector into quantile groups
setup_diff	Setup function for 'diff' arguments
setup_plot	Set up information for a 'GenericML()' plot
setup_stratify	Setup function for stratified sampling
setup_vcov	Setup function for 'vcov_control' arguments
setup_X1	Setup function controlling the matrix X_1 in the BLP or GATES regression
TrueIfUnix	Check if user's OS is a Unix system