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CRE  

Interpretable Discovery and Inference of Heterogeneous Treatment Effects
View on CRAN: Click here


Download and install CRE package within the R console
Install from CRAN:
install.packages("CRE")

Install from Github:
library("remotes")
install_github("cran/CRE")

Install by package version:
library("remotes")
install_version("CRE", "0.2.7")



Attach the package and use:
library("CRE")
Maintained by
Falco Joannes Bargagli Stoffi
[Scholar Profile | Author Map]
First Published: 2022-10-18
Latest Update: 2023-06-14
Description:
Provides a new method for interpretable heterogeneous treatment effects characterization in terms of decision rules via an extensive exploration of heterogeneity patterns by an ensemble-of-trees approach, enforcing high stability in the discovery. It relies on a two-stage pseudo-outcome regression, and it is supported by theoretical convergence guarantees. Bargagli-Stoffi, F. J., Cadei, R., Lee, K., & Dominici, F. (2023) Causal rule ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment Effects. arXiv preprint .
How to cite:
Falco Joannes Bargagli Stoffi (2022). CRE: Interpretable Discovery and Inference of Heterogeneous Treatment Effects. R package version 0.2.7, https://cran.r-project.org/web/packages/CRE. Accessed 06 May. 2025.
Previous versions and publish date:
0.1.0 (2022-10-18 08:35), 0.1.1 (2022-10-22 14:48), 0.2.0 (2023-01-19 21:20), 0.2.1 (2023-03-17 18:20), 0.2.2 (2023-04-17 16:50), 0.2.3 (2023-04-27 22:20), 0.2.4 (2023-06-15 01:12), 0.2.5 (2023-12-06 20:50), 0.2.6 (2024-04-21 23:12)
Other packages that cited CRE R package
View CRE citation profile
Other R packages that CRE depends, imports, suggests or enhances
Complete documentation for CRE
Functions, R codes and Examples using the CRE R package
Some associated functions: CRE-package . autoplot.cre . check_hyper_params . check_input_data . check_method_params . cre . discover_rules . estimate_cate . estimate_ite . estimate_ite_aipw . estimate_ite_bart . estimate_ite_bcf . estimate_ite_cf . estimate_ite_slearner . estimate_ite_tlearner . estimate_ite_tpoisson . estimate_ite_xlearner . estimate_ps . evaluate . extract_effect_modifiers . extract_rules . filter_correlated_rules . filter_extreme_rules . filter_irrelevant_rules . generate_cre_dataset . generate_rules . generate_rules_matrix . get_logger . honest_splitting . interpret_rules . plot.cre . print.cre . select_rules . set_logger . standardize_rules_matrix . summary.cre . 
Some associated R codes: CRE_package.R . check_hyper_params.R . check_input_data.R . check_method_params.R . cre.R . discover_rules.R . estimate_cate.R . estimate_ite.R . estimate_ite_aipw.R . estimate_ite_bart.R . estimate_ite_bcf.R . estimate_ite_cf.R . estimate_ite_slearner.R . estimate_ite_tlearner.R . estimate_ite_tpoisson.R . estimate_ite_xlearner.R . estimate_ps.R . evaluate.R . extract_effect_modifiers.R . extract_rules.R . filter_correlated_rules.R . filter_extreme_rules.R . filter_irrelevant_rules.R . generate_cre_dataset.R . generate_rules.R . generate_rules_matrix.R . honest_splitting.R . interpret_rules.R . logger_utils.R . plot.R . print.R . select_rules.R . utils.R . zzz.R .  Full CRE package functions and examples
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