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- vignettes added for policy_data, policy_learn and policy_eval.- new policy_learn type: "blip". Similar to "drql", but only a single model is fitted using the doubly robust score for the blip.
- q_sl now uses the folds from policy_learn when it is used a policy model for "blip" and "drql".
- g_xgboost and q_xgboost.- action sets can now vary across stages (stage_action_sets)
- g_empir() is a new g-model useful for calculating the empirical (conditional)
probabilities
- conditional() estimates the group specific policy value estimates
- progressr is now implemented for policy_eval()
- sim_single_stage(), sim_two_stage(), and sim_multi_stage() are new functions
for simulating data.- Package documentation: https://arxiv.org/abs/2212.02335These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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