rerun ate sensitivity simulation

Author: SvenKlaassen

results/irm/irm_ate_sensitivity.csv

@@ -0,0 +1,53 @@
+simulation_parameters:
+  repetitions: 500
+  max_runtime: 19800
+  random_seed: 42
+  n_jobs: -2
+dgp_parameters:
+  theta:
+  - 5.0
+  n_obs:
+  - 5000
+  trimming_threshold:
+  - 0.05
+  var_epsilon_y:
+  - 1.0
+  linear:
+  - false
+  gamma_a:
+  - 0.198
+  beta_a:
+  - 0.582
+learner_definitions:
+  linear: &id001
+    name: Linear
+  logit: &id002
+    name: Logistic
+  lgbmr: &id003
+    name: LGBM Regr.
+    params:
+      n_estimators: 500
+      learning_rate: 0.01
+      min_child_samples: 10
+  lgbmc: &id004
+    name: LGBM Clas.
+    params:
+      n_estimators: 500
+      learning_rate: 0.01
+      min_child_samples: 10
+dml_parameters:
+  learners:
+  - ml_g: *id001
+    ml_m: *id002
+  - ml_g: *id003
+    ml_m: *id004
+  - ml_g: *id003
+    ml_m: *id002
+  - ml_g: *id001
+    ml_m: *id004
+  trimming_threshold:
+  - 0.05
+confidence_parameters:
+  level:
+  - 0.95
+  - 0.9

results/irm/irm_ate_sensitivity_config.yml

@@ -0,0 +1,9 @@
+Learner g,Learner m,level,Coverage,CI Length,Bias,Coverage (Lower),Coverage (Upper),RV,RVa,Bias (Lower),Bias (Upper),repetition
+LGBM Regr.,LGBM Clas.,0.9,0.104,0.2668157568060522,0.18026525524152154,0.966,1.0,0.12473788062439613,0.05508904509343494,0.04380159419714633,0.3234512135135403,500
+LGBM Regr.,LGBM Clas.,0.95,0.276,0.31793058377898364,0.18026525524152154,1.0,1.0,0.12473788062439613,0.03540613542014128,0.04380159419714633,0.3234512135135403,500
+LGBM Regr.,Logistic,0.9,0.248,0.25763009474845106,0.14980027719730954,0.998,1.0,0.10093696287018208,0.03536055959101725,0.027371865522670537,0.2987135019044584,500
+LGBM Regr.,Logistic,0.95,0.552,0.306985192339855,0.14980027719730954,1.0,1.0,0.10093696287018208,0.01878662839660344,0.027371865522670537,0.2987135019044584,500
+Linear,LGBM Clas.,0.9,0.112,0.26715210077204105,0.17865402724192433,0.962,1.0,0.12630248546657805,0.055046351043189806,0.04436057060203107,0.31869461365134216,500
+Linear,LGBM Clas.,0.95,0.282,0.318331362333959,0.17865402724192433,0.998,1.0,0.12630248546657805,0.03487837647302397,0.04436057060203107,0.31869461365134216,500
+Linear,Logistic,0.9,0.852,0.2589605314211221,0.09016543407251673,1.0,1.0,0.06325807709105473,0.00696464260372732,0.05686871205333632,0.23561615221802584,500
+Linear,Logistic,0.95,0.978,0.30857050541538944,0.09016543407251673,1.0,1.0,0.06325807709105473,0.0015852998947931969,0.05686871205333632,0.23561615221802584,500

results/irm/irm_ate_sensitivity_coverage.csv

@@ -1,2 +1,2 @@
-DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.10.dev0,irm_ate_sensitivity.py,2025-05-22 14:48:09,6858.955473899841,3.12.10
+DoubleML Version,Script,Date,Total Runtime (minutes),Python Version,Config File
+0.10.0,IRMATESensitivityCoverageSimulation,2025-06-04 10:16,29.540068797270457,3.12.3,scripts/irm/irm_ate_sensitivity_config.yml

results/irm/irm_ate_sensitivity_metadata.csv

@@ -1,7 +1,7 @@
-# Simulation parameters for IRM ATE Coverage
+# Simulation parameters for IRM ATE Sensitivity Coverage
 
 simulation_parameters:
-  repetitions: 10
+  repetitions: 500
   max_runtime: 19800 # 5.5 hours in seconds
   random_seed: 42
   n_jobs: -2