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0.16.0
  • EconML User Guide
    • Overview
    • Machine Learning Based Estimation of Heterogeneous Treatment Effects
    • Motivating Examples
      • Recommendation A/B testing
      • Customer Segmentation
      • Multi-investment Attribution
    • Introduction to Causal Inference
    • Problem Setup and API Design
      • API of Conditional Average Treatment Effect Package
      • Linear in Treatment CATE Estimators
      • Example Use of API
    • Library Flow Chart
    • Detailed estimator comparison
    • Estimation Methods under Unconfoundedness
      • Orthogonal/Double Machine Learning
        • What is it?
        • What are the relevant estimator classes?
        • When should you use it?
        • Overview of Formal Methodology
        • Class Hierarchy Structure
        • Usage FAQs
        • Usage Examples
      • Doubly Robust Learning
        • What is it?
        • What are the relevant estimator classes?
        • When should you use it?
        • Overview of Formal Methodology
        • Class Hierarchy Structure
        • Usage FAQs
        • Usage Examples
      • Forest Based Estimators
        • What is it?
        • What are the relevant estimator classes?
        • When should you use it?
        • Overview of Formal Methodology
        • Class Hierarchy Structure
        • Usage Examples
      • Meta-Learners
        • What is it?
        • What are the relevant estimator classes?
        • When should you use it?
        • Overview of Formal Methodology
        • Class Hierarchy Structure
        • Usage Examples
    • Estimation Methods with Instruments
      • Sieve 2SLS Instrumental Variable Estimation
      • Orthogonal instrumental variables
        • What is it?
        • What are the relevant estimator classes?
        • When should you use it?
        • Class Hierarchy Structure
        • Usage Examples
    • Estimation Methods for Dynamic Treatment Regimes
      • Dynamic Double Machine Learning
        • What is it?
        • What are the relevant estimator classes?
        • When should you use it?
        • Class Hierarchy Structure
        • Usage FAQs
    • Inference
      • Bootstrap Inference
      • OLS Inference
      • Debiased Lasso Inference
      • Subsampled Honest Forest Inference
      • OrthoForest Bootstrap of Little Bags Inference
    • Model Selection
    • Validation
      • Sensitivity Analysis
      • DRTester
      • Scoring
      • Confidence Intervals and Inference
      • DoWhy Refutation Tests
    • Interpretability
      • Tree Interpreter
      • Policy Interpreter
      • SHAP
    • Federated Learning in EconML
      • Overview
      • Motivation for Incorporating Federated Learning into the EconML Library
      • Federated Learning with EconML
        • Introducing the FederatedEstimator
        • Example Usage
      • Theory
    • References
    • Frequently Asked Questions (FAQ)
      • When should I use EconML?
      • What are the advantages of EconML?
      • How do I know if the results make sense?
      • I’m getting causal estimates that don’t make sense. What next?
      • What if I don’t have a good instrument, can’t run an experiment, and don’t observe all confounders?
      • How can I test whether I’m identifying the causal effect?
      • How do I give feedback?
    • Community
  • Public Module Reference
    • CATE Estimators
      • Double Machine Learning (DML)
        • econml.dml.DML
        • econml.dml.LinearDML
        • econml.dml.SparseLinearDML
        • econml.dml.CausalForestDML
        • econml.dml.NonParamDML
        • econml.dml.KernelDML
      • Doubly Robust (DR)
        • econml.dr.DRLearner
        • econml.dr.LinearDRLearner
        • econml.dr.SparseLinearDRLearner
        • econml.dr.ForestDRLearner
      • Meta-Learners
        • econml.metalearners.XLearner
        • econml.metalearners.TLearner
        • econml.metalearners.SLearner
        • econml.metalearners.DomainAdaptationLearner
      • Orthogonal Random Forest (ORF)
        • econml.orf.DMLOrthoForest
        • econml.orf.DROrthoForest
    • Instrumental Variable CATE Estimators
      • Double Machine Learning (DML) IV
        • econml.iv.dml.OrthoIV
        • econml.iv.dml.DMLIV
        • econml.iv.dml.NonParamDMLIV
      • Doubly Robust (DR) IV
        • econml.iv.dr.DRIV
        • econml.iv.dr.LinearDRIV
        • econml.iv.dr.SparseLinearDRIV
        • econml.iv.dr.ForestDRIV
        • econml.iv.dr.IntentToTreatDRIV
        • econml.iv.dr.LinearIntentToTreatDRIV
      • Sieve Methods
        • econml.iv.sieve.SieveTSLS
        • econml.iv.sieve.HermiteFeatures
        • econml.iv.sieve.DPolynomialFeatures
    • Estimators for Panel Data
      • Dynamic Double Machine Learning
        • econml.panel.dml.DynamicDML
    • Policy Learning
      • econml.policy.DRPolicyForest
        • DRPolicyForest
      • econml.policy.DRPolicyTree
        • DRPolicyTree
      • econml.policy.PolicyForest
        • PolicyForest
      • econml.policy.PolicyTree
        • PolicyTree
    • CATE Interpreters
      • econml.cate_interpreter.SingleTreeCateInterpreter
        • SingleTreeCateInterpreter
      • econml.cate_interpreter.SingleTreePolicyInterpreter
        • SingleTreePolicyInterpreter
    • CATE Validation
      • econml.validate.DRTester
        • DRTester
      • econml.validate.BLPEvaluationResults
        • BLPEvaluationResults
      • econml.validate.CalibrationEvaluationResults
        • CalibrationEvaluationResults
      • econml.validate.UpliftEvaluationResults
        • UpliftEvaluationResults
      • econml.validate.EvaluationResults
        • EvaluationResults
    • CATE Scorers
      • econml.score.RScorer
        • RScorer
      • econml.score.EnsembleCateEstimator
        • EnsembleCateEstimator
    • Generalized Random Forests
      • econml.grf.CausalForest
        • CausalForest
      • econml.grf.CausalIVForest
        • CausalIVForest
      • econml.grf.RegressionForest
        • RegressionForest
      • econml.grf.MultiOutputGRF
        • MultiOutputGRF
      • econml.grf.LinearMomentGRFCriterion
        • LinearMomentGRFCriterion
      • econml.grf.LinearMomentGRFCriterionMSE
        • LinearMomentGRFCriterionMSE
      • econml.grf._base_grf.BaseGRF
        • BaseGRF
      • econml.grf._base_grftree.GRFTree
        • GRFTree
    • Scikit-Learn Extensions
      • Linear Model Extensions
        • econml.sklearn_extensions.linear_model.DebiasedLasso
        • econml.sklearn_extensions.linear_model.MultiOutputDebiasedLasso
        • econml.sklearn_extensions.linear_model.SelectiveRegularization
        • econml.sklearn_extensions.linear_model.StatsModelsLinearRegression
        • econml.sklearn_extensions.linear_model.StatsModelsRLM
        • econml.sklearn_extensions.linear_model.WeightedLasso
        • econml.sklearn_extensions.linear_model.WeightedLassoCV
        • econml.sklearn_extensions.linear_model.WeightedMultiTaskLassoCV
        • econml.sklearn_extensions.linear_model.WeightedLassoCVWrapper
      • Model Selection Extensions
        • econml.sklearn_extensions.model_selection.GridSearchCVList
        • econml.sklearn_extensions.model_selection.WeightedKFold
        • econml.sklearn_extensions.model_selection.WeightedStratifiedKFold
    • Inference
      • Inference Results
        • econml.inference.NormalInferenceResults
        • econml.inference.EmpiricalInferenceResults
        • econml.inference.PopulationSummaryResults
      • Inference Methods
        • econml.inference.BootstrapInference
        • econml.inference.GenericModelFinalInference
        • econml.inference.GenericSingleTreatmentModelFinalInference
        • econml.inference.LinearModelFinalInference
        • econml.inference.StatsModelsInference
        • econml.inference.GenericModelFinalInferenceDiscrete
        • econml.inference.LinearModelFinalInferenceDiscrete
        • econml.inference.StatsModelsInferenceDiscrete
    • Federated Estimation
      • econml.federated_learning.FederatedEstimator
        • FederatedEstimator
    • Solutions
      • Causal Analysis
        • econml.solutions.causal_analysis.CausalAnalysis
    • Integration with DoWhy
      • econml.dowhy.DoWhyWrapper
        • DoWhyWrapper
    • Utilities
      • econml.utilities
        • IdentityFeatures
        • MissingModule
        • MultiModelWrapper
        • SeparateModel
        • Summary
        • WeightedModelWrapper
        • add_intercept()
        • broadcast_unit_treatments()
        • check_input_arrays()
        • check_inputs()
        • check_models()
        • concatenate()
        • cross_product()
        • deprecated()
        • einsum_sparse()
        • filter_none_kwargs()
        • get_feature_names_or_default()
        • get_input_columns()
        • hstack()
        • inverse_onehot()
        • iscoo()
        • issparse()
        • jacify_featurizer()
        • ndim()
        • one_hot_encoder()
        • reshape()
        • reshape_Y_T()
        • reshape_arrays_2dim()
        • reshape_outcomewise_effects()
        • reshape_treatmentwise_effects()
        • shape()
        • size()
        • stack()
        • strata_from_discrete_arrays()
        • tensordot()
        • tocoo()
        • todense()
        • transpose()
        • transpose_dictionary()
        • vstack()
  • Private Module Reference
    • econml._ortho_learner
      • CachedValues
        • CachedValues.count()
        • CachedValues.index()
        • CachedValues.T
        • CachedValues.W
        • CachedValues.X
        • CachedValues.Y
        • CachedValues.Z
        • CachedValues.freq_weight
        • CachedValues.groups
        • CachedValues.nuisances
        • CachedValues.sample_var
        • CachedValues.sample_weight
      • _OrthoLearner
        • _OrthoLearner.models_nuisance_
        • _OrthoLearner.ortho_learner_model_final_
        • _OrthoLearner.score_
        • _OrthoLearner.nuisance_scores_
        • _OrthoLearner.ate()
        • _OrthoLearner.ate_inference()
        • _OrthoLearner.ate_interval()
        • _OrthoLearner.cate_feature_names()
        • _OrthoLearner.cate_output_names()
        • _OrthoLearner.cate_treatment_names()
        • _OrthoLearner.const_marginal_ate()
        • _OrthoLearner.const_marginal_ate_inference()
        • _OrthoLearner.const_marginal_ate_interval()
        • _OrthoLearner.const_marginal_effect()
        • _OrthoLearner.const_marginal_effect_inference()
        • _OrthoLearner.const_marginal_effect_interval()
        • _OrthoLearner.effect()
        • _OrthoLearner.effect_inference()
        • _OrthoLearner.effect_interval()
        • _OrthoLearner.fit()
        • _OrthoLearner.marginal_ate()
        • _OrthoLearner.marginal_ate_inference()
        • _OrthoLearner.marginal_ate_interval()
        • _OrthoLearner.marginal_effect()
        • _OrthoLearner.marginal_effect_inference()
        • _OrthoLearner.marginal_effect_interval()
        • _OrthoLearner.refit_final()
        • _OrthoLearner.score()
        • _OrthoLearner.shap_values()
        • _OrthoLearner.dowhy
      • _crossfit()
    • econml._cate_estimator
      • BaseCateEstimator
        • BaseCateEstimator.ate()
        • BaseCateEstimator.ate_inference()
        • BaseCateEstimator.ate_interval()
        • BaseCateEstimator.cate_feature_names()
        • BaseCateEstimator.cate_output_names()
        • BaseCateEstimator.cate_treatment_names()
        • BaseCateEstimator.effect()
        • BaseCateEstimator.effect_inference()
        • BaseCateEstimator.effect_interval()
        • BaseCateEstimator.fit()
        • BaseCateEstimator.marginal_ate()
        • BaseCateEstimator.marginal_ate_inference()
        • BaseCateEstimator.marginal_ate_interval()
        • BaseCateEstimator.marginal_effect()
        • BaseCateEstimator.marginal_effect_inference()
        • BaseCateEstimator.marginal_effect_interval()
        • BaseCateEstimator.dowhy
      • DebiasedLassoCateEstimatorDiscreteMixin
        • DebiasedLassoCateEstimatorDiscreteMixin.ate()
        • DebiasedLassoCateEstimatorDiscreteMixin.ate_inference()
        • DebiasedLassoCateEstimatorDiscreteMixin.ate_interval()
        • DebiasedLassoCateEstimatorDiscreteMixin.cate_feature_names()
        • DebiasedLassoCateEstimatorDiscreteMixin.cate_output_names()
        • DebiasedLassoCateEstimatorDiscreteMixin.cate_treatment_names()
        • DebiasedLassoCateEstimatorDiscreteMixin.coef_()
        • DebiasedLassoCateEstimatorDiscreteMixin.coef__inference()
        • DebiasedLassoCateEstimatorDiscreteMixin.coef__interval()
        • DebiasedLassoCateEstimatorDiscreteMixin.effect()
        • DebiasedLassoCateEstimatorDiscreteMixin.effect_inference()
        • DebiasedLassoCateEstimatorDiscreteMixin.effect_interval()
        • DebiasedLassoCateEstimatorDiscreteMixin.fit()
        • DebiasedLassoCateEstimatorDiscreteMixin.intercept_()
        • DebiasedLassoCateEstimatorDiscreteMixin.intercept__inference()
        • DebiasedLassoCateEstimatorDiscreteMixin.intercept__interval()
        • DebiasedLassoCateEstimatorDiscreteMixin.marginal_ate()
        • DebiasedLassoCateEstimatorDiscreteMixin.marginal_ate_inference()
        • DebiasedLassoCateEstimatorDiscreteMixin.marginal_ate_interval()
        • DebiasedLassoCateEstimatorDiscreteMixin.marginal_effect()
        • DebiasedLassoCateEstimatorDiscreteMixin.marginal_effect_inference()
        • DebiasedLassoCateEstimatorDiscreteMixin.marginal_effect_interval()
        • DebiasedLassoCateEstimatorDiscreteMixin.summary()
        • DebiasedLassoCateEstimatorDiscreteMixin.dowhy
      • DebiasedLassoCateEstimatorMixin
        • DebiasedLassoCateEstimatorMixin.ate()
        • DebiasedLassoCateEstimatorMixin.ate_inference()
        • DebiasedLassoCateEstimatorMixin.ate_interval()
        • DebiasedLassoCateEstimatorMixin.cate_feature_names()
        • DebiasedLassoCateEstimatorMixin.cate_output_names()
        • DebiasedLassoCateEstimatorMixin.cate_treatment_names()
        • DebiasedLassoCateEstimatorMixin.coef__inference()
        • DebiasedLassoCateEstimatorMixin.coef__interval()
        • DebiasedLassoCateEstimatorMixin.effect()
        • DebiasedLassoCateEstimatorMixin.effect_inference()
        • DebiasedLassoCateEstimatorMixin.effect_interval()
        • DebiasedLassoCateEstimatorMixin.fit()
        • DebiasedLassoCateEstimatorMixin.intercept__inference()
        • DebiasedLassoCateEstimatorMixin.intercept__interval()
        • DebiasedLassoCateEstimatorMixin.marginal_ate()
        • DebiasedLassoCateEstimatorMixin.marginal_ate_inference()
        • DebiasedLassoCateEstimatorMixin.marginal_ate_interval()
        • DebiasedLassoCateEstimatorMixin.marginal_effect()
        • DebiasedLassoCateEstimatorMixin.marginal_effect_inference()
        • DebiasedLassoCateEstimatorMixin.marginal_effect_interval()
        • DebiasedLassoCateEstimatorMixin.shap_values()
        • DebiasedLassoCateEstimatorMixin.summary()
        • DebiasedLassoCateEstimatorMixin.coef_
        • DebiasedLassoCateEstimatorMixin.dowhy
        • DebiasedLassoCateEstimatorMixin.intercept_
      • ForestModelFinalCateEstimatorDiscreteMixin
        • ForestModelFinalCateEstimatorDiscreteMixin.ate()
        • ForestModelFinalCateEstimatorDiscreteMixin.ate_inference()
        • ForestModelFinalCateEstimatorDiscreteMixin.ate_interval()
        • ForestModelFinalCateEstimatorDiscreteMixin.cate_feature_names()
        • ForestModelFinalCateEstimatorDiscreteMixin.cate_output_names()
        • ForestModelFinalCateEstimatorDiscreteMixin.cate_treatment_names()
        • ForestModelFinalCateEstimatorDiscreteMixin.effect()
        • ForestModelFinalCateEstimatorDiscreteMixin.effect_inference()
        • ForestModelFinalCateEstimatorDiscreteMixin.effect_interval()
        • ForestModelFinalCateEstimatorDiscreteMixin.fit()
        • ForestModelFinalCateEstimatorDiscreteMixin.marginal_ate()
        • ForestModelFinalCateEstimatorDiscreteMixin.marginal_ate_inference()
        • ForestModelFinalCateEstimatorDiscreteMixin.marginal_ate_interval()
        • ForestModelFinalCateEstimatorDiscreteMixin.marginal_effect()
        • ForestModelFinalCateEstimatorDiscreteMixin.marginal_effect_inference()
        • ForestModelFinalCateEstimatorDiscreteMixin.marginal_effect_interval()
        • ForestModelFinalCateEstimatorDiscreteMixin.dowhy
      • ForestModelFinalCateEstimatorMixin
        • ForestModelFinalCateEstimatorMixin.ate()
        • ForestModelFinalCateEstimatorMixin.ate_inference()
        • ForestModelFinalCateEstimatorMixin.ate_interval()
        • ForestModelFinalCateEstimatorMixin.cate_feature_names()
        • ForestModelFinalCateEstimatorMixin.cate_output_names()
        • ForestModelFinalCateEstimatorMixin.cate_treatment_names()
        • ForestModelFinalCateEstimatorMixin.effect()
        • ForestModelFinalCateEstimatorMixin.effect_inference()
        • ForestModelFinalCateEstimatorMixin.effect_interval()
        • ForestModelFinalCateEstimatorMixin.fit()
        • ForestModelFinalCateEstimatorMixin.marginal_ate()
        • ForestModelFinalCateEstimatorMixin.marginal_ate_inference()
        • ForestModelFinalCateEstimatorMixin.marginal_ate_interval()
        • ForestModelFinalCateEstimatorMixin.marginal_effect()
        • ForestModelFinalCateEstimatorMixin.marginal_effect_inference()
        • ForestModelFinalCateEstimatorMixin.marginal_effect_interval()
        • ForestModelFinalCateEstimatorMixin.dowhy
      • LinearCateEstimator
        • LinearCateEstimator.ate()
        • LinearCateEstimator.ate_inference()
        • LinearCateEstimator.ate_interval()
        • LinearCateEstimator.cate_feature_names()
        • LinearCateEstimator.cate_output_names()
        • LinearCateEstimator.cate_treatment_names()
        • LinearCateEstimator.const_marginal_ate()
        • LinearCateEstimator.const_marginal_ate_inference()
        • LinearCateEstimator.const_marginal_ate_interval()
        • LinearCateEstimator.const_marginal_effect()
        • LinearCateEstimator.const_marginal_effect_inference()
        • LinearCateEstimator.const_marginal_effect_interval()
        • LinearCateEstimator.effect()
        • LinearCateEstimator.effect_inference()
        • LinearCateEstimator.effect_interval()
        • LinearCateEstimator.fit()
        • LinearCateEstimator.marginal_ate()
        • LinearCateEstimator.marginal_ate_inference()
        • LinearCateEstimator.marginal_ate_interval()
        • LinearCateEstimator.marginal_effect()
        • LinearCateEstimator.marginal_effect_inference()
        • LinearCateEstimator.marginal_effect_interval()
        • LinearCateEstimator.shap_values()
        • LinearCateEstimator.dowhy
      • LinearModelFinalCateEstimatorDiscreteMixin
        • LinearModelFinalCateEstimatorDiscreteMixin.ate()
        • LinearModelFinalCateEstimatorDiscreteMixin.ate_inference()
        • LinearModelFinalCateEstimatorDiscreteMixin.ate_interval()
        • LinearModelFinalCateEstimatorDiscreteMixin.cate_feature_names()
        • LinearModelFinalCateEstimatorDiscreteMixin.cate_output_names()
        • LinearModelFinalCateEstimatorDiscreteMixin.cate_treatment_names()
        • LinearModelFinalCateEstimatorDiscreteMixin.coef_()
        • LinearModelFinalCateEstimatorDiscreteMixin.coef__inference()
        • LinearModelFinalCateEstimatorDiscreteMixin.coef__interval()
        • LinearModelFinalCateEstimatorDiscreteMixin.effect()
        • LinearModelFinalCateEstimatorDiscreteMixin.effect_inference()
        • LinearModelFinalCateEstimatorDiscreteMixin.effect_interval()
        • LinearModelFinalCateEstimatorDiscreteMixin.fit()
        • LinearModelFinalCateEstimatorDiscreteMixin.intercept_()
        • LinearModelFinalCateEstimatorDiscreteMixin.intercept__inference()
        • LinearModelFinalCateEstimatorDiscreteMixin.intercept__interval()
        • LinearModelFinalCateEstimatorDiscreteMixin.marginal_ate()
        • LinearModelFinalCateEstimatorDiscreteMixin.marginal_ate_inference()
        • LinearModelFinalCateEstimatorDiscreteMixin.marginal_ate_interval()
        • LinearModelFinalCateEstimatorDiscreteMixin.marginal_effect()
        • LinearModelFinalCateEstimatorDiscreteMixin.marginal_effect_inference()
        • LinearModelFinalCateEstimatorDiscreteMixin.marginal_effect_interval()
        • LinearModelFinalCateEstimatorDiscreteMixin.summary()
        • LinearModelFinalCateEstimatorDiscreteMixin.dowhy
      • LinearModelFinalCateEstimatorMixin
        • LinearModelFinalCateEstimatorMixin.bias_part_of_coef
        • LinearModelFinalCateEstimatorMixin.ate()
        • LinearModelFinalCateEstimatorMixin.ate_inference()
        • LinearModelFinalCateEstimatorMixin.ate_interval()
        • LinearModelFinalCateEstimatorMixin.cate_feature_names()
        • LinearModelFinalCateEstimatorMixin.cate_output_names()
        • LinearModelFinalCateEstimatorMixin.cate_treatment_names()
        • LinearModelFinalCateEstimatorMixin.coef__inference()
        • LinearModelFinalCateEstimatorMixin.coef__interval()
        • LinearModelFinalCateEstimatorMixin.effect()
        • LinearModelFinalCateEstimatorMixin.effect_inference()
        • LinearModelFinalCateEstimatorMixin.effect_interval()
        • LinearModelFinalCateEstimatorMixin.fit()
        • LinearModelFinalCateEstimatorMixin.intercept__inference()
        • LinearModelFinalCateEstimatorMixin.intercept__interval()
        • LinearModelFinalCateEstimatorMixin.marginal_ate()
        • LinearModelFinalCateEstimatorMixin.marginal_ate_inference()
        • LinearModelFinalCateEstimatorMixin.marginal_ate_interval()
        • LinearModelFinalCateEstimatorMixin.marginal_effect()
        • LinearModelFinalCateEstimatorMixin.marginal_effect_inference()
        • LinearModelFinalCateEstimatorMixin.marginal_effect_interval()
        • LinearModelFinalCateEstimatorMixin.shap_values()
        • LinearModelFinalCateEstimatorMixin.summary()
        • LinearModelFinalCateEstimatorMixin.coef_
        • LinearModelFinalCateEstimatorMixin.dowhy
        • LinearModelFinalCateEstimatorMixin.intercept_
      • StatsModelsCateEstimatorDiscreteMixin
        • StatsModelsCateEstimatorDiscreteMixin.ate()
        • StatsModelsCateEstimatorDiscreteMixin.ate_inference()
        • StatsModelsCateEstimatorDiscreteMixin.ate_interval()
        • StatsModelsCateEstimatorDiscreteMixin.cate_feature_names()
        • StatsModelsCateEstimatorDiscreteMixin.cate_output_names()
        • StatsModelsCateEstimatorDiscreteMixin.cate_treatment_names()
        • StatsModelsCateEstimatorDiscreteMixin.coef_()
        • StatsModelsCateEstimatorDiscreteMixin.coef__inference()
        • StatsModelsCateEstimatorDiscreteMixin.coef__interval()
        • StatsModelsCateEstimatorDiscreteMixin.effect()
        • StatsModelsCateEstimatorDiscreteMixin.effect_inference()
        • StatsModelsCateEstimatorDiscreteMixin.effect_interval()
        • StatsModelsCateEstimatorDiscreteMixin.fit()
        • StatsModelsCateEstimatorDiscreteMixin.intercept_()
        • StatsModelsCateEstimatorDiscreteMixin.intercept__inference()
        • StatsModelsCateEstimatorDiscreteMixin.intercept__interval()
        • StatsModelsCateEstimatorDiscreteMixin.marginal_ate()
        • StatsModelsCateEstimatorDiscreteMixin.marginal_ate_inference()
        • StatsModelsCateEstimatorDiscreteMixin.marginal_ate_interval()
        • StatsModelsCateEstimatorDiscreteMixin.marginal_effect()
        • StatsModelsCateEstimatorDiscreteMixin.marginal_effect_inference()
        • StatsModelsCateEstimatorDiscreteMixin.marginal_effect_interval()
        • StatsModelsCateEstimatorDiscreteMixin.summary()
        • StatsModelsCateEstimatorDiscreteMixin.dowhy
      • StatsModelsCateEstimatorMixin
        • StatsModelsCateEstimatorMixin.ate()
        • StatsModelsCateEstimatorMixin.ate_inference()
        • StatsModelsCateEstimatorMixin.ate_interval()
        • StatsModelsCateEstimatorMixin.cate_feature_names()
        • StatsModelsCateEstimatorMixin.cate_output_names()
        • StatsModelsCateEstimatorMixin.cate_treatment_names()
        • StatsModelsCateEstimatorMixin.coef__inference()
        • StatsModelsCateEstimatorMixin.coef__interval()
        • StatsModelsCateEstimatorMixin.effect()
        • StatsModelsCateEstimatorMixin.effect_inference()
        • StatsModelsCateEstimatorMixin.effect_interval()
        • StatsModelsCateEstimatorMixin.fit()
        • StatsModelsCateEstimatorMixin.intercept__inference()
        • StatsModelsCateEstimatorMixin.intercept__interval()
        • StatsModelsCateEstimatorMixin.marginal_ate()
        • StatsModelsCateEstimatorMixin.marginal_ate_inference()
        • StatsModelsCateEstimatorMixin.marginal_ate_interval()
        • StatsModelsCateEstimatorMixin.marginal_effect()
        • StatsModelsCateEstimatorMixin.marginal_effect_inference()
        • StatsModelsCateEstimatorMixin.marginal_effect_interval()
        • StatsModelsCateEstimatorMixin.shap_values()
        • StatsModelsCateEstimatorMixin.summary()
        • StatsModelsCateEstimatorMixin.coef_
        • StatsModelsCateEstimatorMixin.dowhy
        • StatsModelsCateEstimatorMixin.intercept_
      • TreatmentExpansionMixin
        • TreatmentExpansionMixin.ate()
        • TreatmentExpansionMixin.ate_inference()
        • TreatmentExpansionMixin.ate_interval()
        • TreatmentExpansionMixin.cate_feature_names()
        • TreatmentExpansionMixin.cate_output_names()
        • TreatmentExpansionMixin.cate_treatment_names()
        • TreatmentExpansionMixin.effect()
        • TreatmentExpansionMixin.effect_inference()
        • TreatmentExpansionMixin.effect_interval()
        • TreatmentExpansionMixin.fit()
        • TreatmentExpansionMixin.marginal_ate()
        • TreatmentExpansionMixin.marginal_ate_inference()
        • TreatmentExpansionMixin.marginal_ate_interval()
        • TreatmentExpansionMixin.marginal_effect()
        • TreatmentExpansionMixin.marginal_effect_inference()
        • TreatmentExpansionMixin.marginal_effect_interval()
        • TreatmentExpansionMixin.dowhy
    • econml.dml._rlearner
      • _RLearner
        • _RLearner.models_y
        • _RLearner.models_t
        • _RLearner.rlearner_model_final_
        • _RLearner.score_
        • _RLearner.nuisance_scores_y
        • _RLearner.nuisance_scores_t
        • _RLearner.ate()
        • _RLearner.ate_inference()
        • _RLearner.ate_interval()
        • _RLearner.cate_feature_names()
        • _RLearner.cate_output_names()
        • _RLearner.cate_treatment_names()
        • _RLearner.const_marginal_ate()
        • _RLearner.const_marginal_ate_inference()
        • _RLearner.const_marginal_ate_interval()
        • _RLearner.const_marginal_effect()
        • _RLearner.const_marginal_effect_inference()
        • _RLearner.const_marginal_effect_interval()
        • _RLearner.effect()
        • _RLearner.effect_inference()
        • _RLearner.effect_interval()
        • _RLearner.fit()
        • _RLearner.marginal_ate()
        • _RLearner.marginal_ate_inference()
        • _RLearner.marginal_ate_interval()
        • _RLearner.marginal_effect()
        • _RLearner.marginal_effect_inference()
        • _RLearner.marginal_effect_interval()
        • _RLearner.refit_final()
        • _RLearner.score()
        • _RLearner.score_nuisances()
        • _RLearner.shap_values()
        • _RLearner.dowhy
        • _RLearner.residuals_
    • econml.inference._bootstrap
      • BootstrapEstimator
        • BootstrapEstimator.fit()
econml
  • Overview: module code

All modules for which code is available

  • econml._cate_estimator
  • econml._ortho_learner
  • econml.cate_interpreter._interpreters
  • econml.dml._rlearner
  • econml.dml.causal_forest
  • econml.dml.dml
  • econml.dowhy
  • econml.dr._drlearner
  • econml.federated_learning
  • econml.grf._base_grf
  • econml.grf._base_grftree
  • econml.grf._criterion
  • econml.grf.classes
  • econml.inference._bootstrap
  • econml.inference._inference
  • econml.iv.dml._dml
  • econml.iv.dr._dr
  • econml.iv.sieve._tsls
  • econml.metalearners._metalearners
  • econml.orf._ortho_forest
  • econml.panel.dml._dml
  • econml.policy._drlearner
  • econml.policy._forest._forest
  • econml.policy._forest._tree
  • econml.score.ensemble_cate
  • econml.score.rscorer
  • econml.sklearn_extensions.linear_model
  • econml.sklearn_extensions.model_selection
  • econml.solutions.causal_analysis._causal_analysis
  • econml.utilities
  • econml.validate.drtester
  • econml.validate.results

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