rerun apo sim

Author: SvenKlaassen

results/irm/apo_config.yml

@@ -0,0 +1,49 @@
+simulation_parameters:
+  repetitions: 1000
+  max_runtime: 19800
+  random_seed: 42
+  n_jobs: -2
+dgp_parameters:
+  n_obs:
+  - 500
+  n_levels:
+  - 2
+  linear:
+  - true
+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:
+  treatment_level:
+  - 0
+  - 1
+  - 2
+  trimming_threshold:
+  - 0.01
+  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
+confidence_parameters:
+  level:
+  - 0.95
+  - 0.9

results/irm/apo_coverage.csv

@@ -0,0 +1,25 @@
+Learner g,Learner m,Treatment Level,level,Coverage,CI Length,Bias,repetition
+LGBM Regr.,LGBM Clas.,0,0.9,0.923,8.535462056273152,2.0255827803361752,1000
+LGBM Regr.,LGBM Clas.,0,0.95,0.968,10.170630351290903,2.0255827803361752,1000
+LGBM Regr.,LGBM Clas.,1,0.9,0.915,34.31276092012859,8.463655678765429,1000
+LGBM Regr.,LGBM Clas.,1,0.95,0.969,40.886176442476604,8.463655678765429,1000
+LGBM Regr.,LGBM Clas.,2,0.9,0.901,33.644464659560505,8.44195706768521,1000
+LGBM Regr.,LGBM Clas.,2,0.95,0.953,40.08985233177513,8.44195706768521,1000
+LGBM Regr.,Logistic,0,0.9,0.913,5.611262078064704,1.3129445023644262,1000
+LGBM Regr.,Logistic,0,0.95,0.96,6.686231164049146,1.3129445023644262,1000
+LGBM Regr.,Logistic,1,0.9,0.906,7.131142409013338,1.601689163860689,1000
+LGBM Regr.,Logistic,1,0.95,0.952,8.497280281526653,1.601689163860689,1000
+LGBM Regr.,Logistic,2,0.9,0.926,7.123330875617923,1.5793207930346633,1000
+LGBM Regr.,Logistic,2,0.95,0.961,8.487972265379696,1.5793207930346633,1000
+Linear,LGBM Clas.,0,0.9,0.91,5.450702479855432,1.2788345107461965,1000
+Linear,LGBM Clas.,0,0.95,0.953,6.494912602502952,1.2788345107461965,1000
+Linear,LGBM Clas.,1,0.9,0.934,9.871742629461385,2.0208159577876965,1000
+Linear,LGBM Clas.,1,0.95,0.977,11.762906863787386,2.0208159577876965,1000
+Linear,LGBM Clas.,2,0.9,0.935,7.196139854742809,1.5705772035604926,1000
+Linear,LGBM Clas.,2,0.95,0.971,8.574729515081229,1.5705772035604926,1000
+Linear,Logistic,0,0.9,0.915,5.333252473490304,1.262628265253654,1000
+Linear,Logistic,0,0.95,0.951,6.354962287965668,1.262628265253654,1000
+Linear,Logistic,1,0.9,0.907,5.409257288463179,1.2841258169966927,1000
+Linear,Logistic,1,0.95,0.947,6.445527610957087,1.2841258169966927,1000
+Linear,Logistic,2,0.9,0.909,5.362180231077127,1.2686475779103141,1000
+Linear,Logistic,2,0.95,0.949,6.389431837167295,1.2686475779103141,1000

results/irm/apo_metadata.csv

@@ -0,0 +1,2 @@
+DoubleML Version,Script,Date,Total Runtime (minutes),Python Version,Config File
+0.10.0,APOCoverageSimulation,2025-06-04 15:38,79.44047049681346,3.12.3,scripts/irm/apo_config.yml

results/irm/apos_causal_contrast.csv

@@ -0,0 +1,9 @@
+Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
+LGBM Regr.,LGBM Clas.,0.9,0.95,31.91721104409269,7.529968087228317,1.0,37.4636413071499,10
+LGBM Regr.,LGBM Clas.,0.95,1.0,38.03170270495524,7.529968087228317,1.0,43.241464165962284,10
+LGBM Regr.,Logistic,0.9,0.95,5.304714488934599,1.027836049470268,0.9,6.251613923340696,10
+LGBM Regr.,Logistic,0.95,1.0,6.320957181976872,1.027836049470268,1.0,7.198738181726997,10
+Linear,LGBM Clas.,0.9,1.0,6.438241354759464,1.314536189350619,1.0,7.653944769218363,10
+Linear,LGBM Clas.,0.95,1.0,7.671637750826568,1.314536189350619,1.0,8.702704094524151,10
+Linear,Logistic,0.9,0.85,1.1652765429848944,0.3017518264953267,0.9,1.3833080428519742,10
+Linear,Logistic,0.95,0.95,1.388512642618938,0.3017518264953267,0.9,1.5824304649513923,10

results/irm/apos_config.yml

@@ -0,0 +1,49 @@
+simulation_parameters:
+  repetitions: 10
+  max_runtime: 19800
+  random_seed: 42
+  n_jobs: -2
+dgp_parameters:
+  n_obs:
+  - 500
+  n_levels:
+  - 2
+  linear:
+  - true
+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:
+  treatment_levels:
+  - - 0
+    - 1
+    - 2
+  trimming_threshold:
+  - 0.01
+  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
+confidence_parameters:
+  level:
+  - 0.95
+  - 0.9

results/irm/apos_coverage.csv

@@ -0,0 +1,9 @@
+Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
+LGBM Regr.,LGBM Clas.,0.9,0.9666666666666666,24.23829065815574,5.364818286446242,1.0,30.821279617475888,10
+LGBM Regr.,LGBM Clas.,0.95,1.0,28.88170470514485,5.364818286446242,1.0,34.908362344740716,10
+LGBM Regr.,Logistic,0.9,0.9333333333333333,6.661576667942033,1.3024704354536263,1.0,8.197479425135544,10
+LGBM Regr.,Logistic,0.95,1.0,7.937758190445909,1.3024704354536263,1.0,9.401107266465424,10
+Linear,LGBM Clas.,0.9,1.0,7.396692188822489,1.5391733226732347,1.0,9.104167961217458,10
+Linear,LGBM Clas.,0.95,1.0,8.813702360671227,1.5391733226732347,1.0,10.378182198628407,10
+Linear,Logistic,0.9,0.9666666666666666,5.385540707553376,1.002895084709317,0.9,5.849824289521431,10
+Linear,Logistic,0.95,1.0,6.417267561760002,1.002895084709317,1.0,6.847571899501526,10

results/irm/apos_metadata.csv

@@ -0,0 +1,2 @@
+DoubleML Version,Script,Date,Total Runtime (minutes),Python Version,Config File
+0.10.0,APOSCoverageSimulation,2025-06-04 14:15,0.6359844247500102,3.12.3,scripts/irm/apos_config.yml