Internal base for user-defined randomization inference extensions
Source:R/inference_custom_extensions.R
InferenceCustomRand.RdThis class uses the same fit() result contract as
InferenceCustomAsymp, but only promises estimate/randomization
behavior.
Super class
Inference -> InferenceCustomRand
Methods
+ inherited public methods from Inference
Inference$capabilities()Inference$compute_asymp_confidence_interval()Inference$compute_asymp_two_sided_pval()Inference$compute_exact_confidence_interval()Inference$compute_exact_two_sided_pval_for_treatment_effect()Inference$duplicate()Inference$get_analysis_data()Inference$get_covariates()Inference$get_design_object()Inference$get_model_formula()Inference$get_nonestimable_reason()Inference$get_nonestimable_stage()Inference$get_optimization_alg()Inference$get_response()Inference$get_response_type()Inference$get_treatment()Inference$initialize()Inference$is_nonestimable()Inference$set_optimization_alg()Inference$set_seed()Inference$supports()
InferenceCustomRand$fit()
Calls the user-defined fit callback for this custom inference path; see
InferenceCustomAsymp.
InferenceCustomRand$compute_estimate()
Compute the treatment-effect estimate by delegating to the
user-supplied custom bootstrap estimator. See
InferenceCustomBoot and
InferenceNonParamBootstrap.