cram_estimator: Cram Policy Estimator for Policy Value Difference (Delta)

In cramR: Cram Method for Efficient Simultaneous Learning and Evaluation

Cram Policy Estimator for Policy Value Difference (Delta)

Description

This function returns the cram policy estimator for the policy value difference (delta).

Usage

cram_estimator(X, Y, D, pi, batch_indices, propensity = NULL)

Arguments

X	A matrix or data frame of covariates for each sample.
Y	A vector of outcomes for the n individuals.
D	A vector of binary treatments for the n individuals.
pi	A matrix of n rows and (nb_batch + 1) columns, where n is the sample size and nb_batch is the number of batches, containing the policy assignment for each individual for each policy. The first column represents the baseline policy.
batch_indices	A list where each element is a vector of indices corresponding to the individuals in each batch.
propensity	The propensity score function

Value

The estimated policy value difference (Delta).

cramR documentation built on Aug. 25, 2025, 1:12 a.m.