Update results from script: scripts/irm/irm_apo_coverage.py

Author: github-actions

results/irm/irm_apo_coverage_apo.csv

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+Learner g,Learner m,Treatment Level,level,Coverage,CI Length,Bias,repetition
+LGBM,LGBM,0.0,0.9,0.912,8.657690136121921,2.075985425408154,1000
+LGBM,LGBM,0.0,0.95,0.964,10.316274091547035,2.075985425408154,1000
+LGBM,LGBM,1.0,0.9,0.914,38.23339285821166,9.189360948372517,1000
+LGBM,LGBM,1.0,0.95,0.967,45.55789754237906,9.189360948372517,1000
+LGBM,LGBM,2.0,0.9,0.891,37.49194764946096,9.600729846680576,1000
+LGBM,LGBM,2.0,0.95,0.952,44.67441108385784,9.600729846680576,1000
+LGBM,Logistic,0.0,0.9,0.902,5.625897101886533,1.3356673109449309,1000
+LGBM,Logistic,0.0,0.95,0.956,6.7036698705295725,1.3356673109449309,1000
+LGBM,Logistic,1.0,0.9,0.92,7.423300143143785,1.6958813914305944,1000
+LGBM,Logistic,1.0,0.95,0.968,8.84540769378873,1.6958813914305944,1000
+LGBM,Logistic,2.0,0.9,0.918,7.321275660150268,1.660500602699947,1000
+LGBM,Logistic,2.0,0.95,0.971,8.723838024042964,1.660500602699947,1000
+Linear,LGBM,0.0,0.9,0.901,5.498257423071024,1.305981267915353,1000
+Linear,LGBM,0.0,0.95,0.948,6.551577812380716,1.305981267915353,1000
+Linear,LGBM,1.0,0.9,0.949,10.700720020780512,2.126828037202422,1000
+Linear,LGBM,1.0,0.95,0.982,12.75069435099058,2.126828037202422,1000
+Linear,LGBM,2.0,0.9,0.932,7.513644049429104,1.6342111609274832,1000
+Linear,LGBM,2.0,0.95,0.966,8.953059097926168,1.6342111609274832,1000
+Linear,Logistic,0.0,0.9,0.902,5.335670092717667,1.2845963390782078,1000
+Linear,Logistic,0.0,0.95,0.953,6.357843058957276,1.2845963390782078,1000
+Linear,Logistic,1.0,0.9,0.904,5.417512107920403,1.280503259417172,1000
+Linear,Logistic,1.0,0.95,0.954,6.455363835025866,1.280503259417172,1000
+Linear,Logistic,2.0,0.9,0.907,5.366403391397197,1.2793569219717145,1000
+Linear,Logistic,2.0,0.95,0.96,6.3944640430685675,1.2793569219717145,1000

results/irm/irm_apo_coverage_apos.csv

@@ -0,0 +1,9 @@
+Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
+LGBM,LGBM,0.9,0.9063333333333333,28.21021843292038,7.119510083508661,0.924,36.1943517986729,1000
+LGBM,LGBM,0.95,0.9583333333333334,33.61454856442563,7.119510083508661,0.974,40.868020474452145,1000
+LGBM,Logistic,0.9,0.9173333333333333,6.789316986971467,1.570973449234106,0.923,8.394070597867524,1000
+LGBM,Logistic,0.95,0.963,8.089970168806186,1.570973449234106,0.96,9.592284619044477,1000
+Linear,LGBM,0.9,0.926,7.903418354805325,1.725523010236133,0.939,9.850445774370156,1000
+Linear,LGBM,0.95,0.967,9.41750382912841,1.725523010236133,0.974,11.234392064837424,1000
+Linear,Logistic,0.9,0.9036666666666666,5.372532806955153,1.2795639356934292,0.905,5.7964894175017925,1000
+Linear,Logistic,0.95,0.9573333333333334,6.4017676921854445,1.2795639356934292,0.953,6.8182385960659,1000

results/irm/irm_apo_coverage_apos_contrast.csv

@@ -0,0 +1,9 @@
+Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
+LGBM,LGBM,0.9,0.8885,37.87536523730769,9.787707441089529,0.898,44.828925781533165,1000
+LGBM,LGBM,0.95,0.9485,45.13128131893863,9.787707441089529,0.965,51.42387403222799,1000
+LGBM,Logistic,0.9,0.9275,5.725128733165455,1.267568231095916,0.927,6.774304315459575,1000
+LGBM,Logistic,0.95,0.9625,6.821911652197591,1.267568231095916,0.962,7.7654094416927215,1000
+Linear,LGBM,0.9,0.958,7.430953406859927,1.5065164682583199,0.975,8.798628447594016,1000
+Linear,LGBM,0.95,0.989,8.85452711998085,1.5065164682583199,0.992,10.090116294778499,1000
+Linear,Logistic,0.9,0.873,1.1425883251377777,0.29572275431639516,0.872,1.3505222299078565,1000
+Linear,Logistic,0.95,0.936,1.3614779635902856,0.29572275431639516,0.919,1.5496710496635275,1000

results/irm/irm_apo_coverage_metadata.csv

@@ -0,0 +1,2 @@
+DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
+0.10.dev0,irm_apo_coverage.py,2025-02-03 21:02:12,5798.276986837387,3.12.8