NEWS

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polle 1.6.0

• online estimation/sequential validation for (subgroup) policy evaluation
  • improved functionality for subgroup analysis (subgroup average treatment effect)

polle 1.5.1

• documentation and print method for policy_eval() improved
  • multiple thresholds for policy_learn()
  • bug fixes: get_policy_functions(), predict.blip_function(), predict.q_glmnet()

polle 1.5 (2024-09-06)

• added target argument in policy_eval for estimating the subgroup average treatment effect.
  • added threshold argument in policy_learn for learning the optimal subgroup.
  • added vignette for learning and evaluating the optimal subgroup.

polle 1.4 (2024-04-25)

• vignettes added for policy_data, policy_learn and policy_eval.

polle 1.3 (2023-07-06)

• 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.

polle 1.2 (2023-02-07)

• 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.

polle 1.0 (2022-12-06)

• Package documentation: https://arxiv.org/abs/2212.02335