Merge branch 'p-framework' of https://github.com/DoubleML/doubleml-coverage into p-framework

Author: PhilippBach

results/irm/irm_apo_coverage_apo.csv

@@ -1,25 +1,25 @@
 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
+LGBM,LGBM,0.0,0.9,0.91,8.657690136121921,2.0774322102310396,1000
+LGBM,LGBM,0.0,0.95,0.966,10.316274091547035,2.0774322102310396,1000
+LGBM,LGBM,1.0,0.9,0.914,38.23339285821166,9.221499001374493,1000
+LGBM,LGBM,1.0,0.95,0.967,45.55789754237906,9.221499001374493,1000
+LGBM,LGBM,2.0,0.9,0.894,37.49194764946096,9.569628503931227,1000
+LGBM,LGBM,2.0,0.95,0.953,44.67441108385784,9.569628503931227,1000
+LGBM,Logistic,0.0,0.9,0.903,5.625897101886533,1.3427898044782796,1000
+LGBM,Logistic,0.0,0.95,0.955,6.7036698705295725,1.3427898044782796,1000
+LGBM,Logistic,1.0,0.9,0.924,7.423300143143785,1.6931903229654406,1000
+LGBM,Logistic,1.0,0.95,0.97,8.84540769378873,1.6931903229654406,1000
+LGBM,Logistic,2.0,0.9,0.92,7.321275660150268,1.6627857804697925,1000
+LGBM,Logistic,2.0,0.95,0.965,8.723838024042964,1.6627857804697925,1000
+Linear,LGBM,0.0,0.9,0.902,5.498257423071024,1.31333599452238,1000
+Linear,LGBM,0.0,0.95,0.95,6.551577812380716,1.31333599452238,1000
+Linear,LGBM,1.0,0.9,0.947,10.700720020780512,2.129828839351603,1000
+Linear,LGBM,1.0,0.95,0.983,12.75069435099058,2.129828839351603,1000
+Linear,LGBM,2.0,0.9,0.934,7.513644049429104,1.6381350879200112,1000
+Linear,LGBM,2.0,0.95,0.967,8.953059097926168,1.6381350879200112,1000
+Linear,Logistic,0.0,0.9,0.904,5.335670092717667,1.2923995163085065,1000
+Linear,Logistic,0.0,0.95,0.954,6.357843058957276,1.2923995163085065,1000
+Linear,Logistic,1.0,0.9,0.908,5.417512107920403,1.2807077813820356,1000
+Linear,Logistic,1.0,0.95,0.959,6.455363835025866,1.2807077813820356,1000
+Linear,Logistic,2.0,0.9,0.908,5.366403391397197,1.2885877554305896,1000
+Linear,Logistic,2.0,0.95,0.956,6.3944640430685675,1.2885877554305896,1000

results/irm/irm_apo_coverage_apos.csv

@@ -1,9 +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
+LGBM,LGBM,0.9,0.9066666666666666,28.21021843292038,7.118050410548393,0.925,36.1943517986729,1000
+LGBM,LGBM,0.95,0.958,33.61454856442563,7.118050410548393,0.973,40.868020474452145,1000
+LGBM,Logistic,0.9,0.9136666666666666,6.789316986971467,1.57447223146738,0.921,8.394070597867524,1000
+LGBM,Logistic,0.95,0.9626666666666667,8.089970168806186,1.57447223146738,0.959,9.592284619044477,1000
+Linear,LGBM,0.9,0.9273333333333333,7.903418354805325,1.7307958124719784,0.937,9.850445774370156,1000
+Linear,LGBM,0.95,0.9686666666666667,9.41750382912841,1.7307958124719784,0.975,11.234392064837424,1000
+Linear,Logistic,0.9,0.9053333333333333,5.372532806955153,1.284757885951191,0.902,5.7964894175017925,1000
+Linear,Logistic,0.95,0.9553333333333334,6.4017676921854445,1.284757885951191,0.952,6.8182385960659,1000

results/irm/irm_apo_coverage_apos_contrast.csv

@@ -1,9 +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
+LGBM,LGBM,0.9,0.8885,37.87536523730769,9.786633570698548,0.898,44.828925781533165,1000
+LGBM,LGBM,0.95,0.9485,45.13128131893863,9.786633570698548,0.965,51.42387403222799,1000
+LGBM,Logistic,0.9,0.9275,5.725128733165455,1.2678647082222205,0.926,6.774304315459575,1000
+LGBM,Logistic,0.95,0.962,6.821911652197591,1.2678647082222205,0.961,7.7654094416927215,1000
+Linear,LGBM,0.9,0.958,7.430953406859927,1.5066569199658195,0.975,8.798628447594016,1000
+Linear,LGBM,0.95,0.9885,8.85452711998085,1.5066569199658195,0.992,10.090116294778499,1000
+Linear,Logistic,0.9,0.874,1.1425883251377777,0.2971374642918569,0.871,1.3505222299078565,1000
+Linear,Logistic,0.95,0.934,1.3614779635902856,0.2971374642918569,0.917,1.5496710496635275,1000

results/irm/irm_apo_coverage_metadata.csv

@@ -1,2 +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
+0.10.dev0,irm_apo_coverage.py,2025-02-04 15:18:58,5762.698203086853,3.12.8

results/irm/irm_apo_sensitivity.csv

@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,Coverage (Lower),Coverage (Upper),RV,RVa,Bias (Lower),Bias (Upper),repetition
-LGBM,LGBM,0.9,0.09836065573770492,0.26980333552727825,0.18205252584345485,1.0,1.0,0.09239844030018919,0.04045631137696363,0.035066111350142995,0.3810774239324017,244
-LGBM,LGBM,0.95,0.3073770491803279,0.32149050339653273,0.18205252584345485,1.0,1.0,0.09239844030018919,0.025884873713769935,0.035066111350142995,0.3810774239324017,244
-LGBM,Logistic Regr.,0.9,0.3073770491803279,0.2578060603442706,0.14817801851576512,1.0,1.0,0.07187480682741719,0.024545078956797563,0.06295056021181017,0.35846457343559074,244
-LGBM,Logistic Regr.,0.95,0.5614754098360656,0.30719486827981307,0.14817801851576512,1.0,1.0,0.07187480682741719,0.012961043152938044,0.06295056021181017,0.35846457343559074,244
-Linear Reg.,LGBM,0.9,0.10655737704918032,0.26955592225259073,0.18010332737150503,1.0,1.0,0.0941627548347164,0.04084948000316684,0.03472113416565001,0.37380556783576596,244
-Linear Reg.,LGBM,0.95,0.29918032786885246,0.3211956922961776,0.18010332737150503,1.0,1.0,0.0941627548347164,0.026040282694101653,0.03472113416565001,0.37380556783576596,244
-Linear Reg.,Logistic Regr.,0.9,0.8852459016393442,0.25925313646720843,0.08765249652827344,1.0,1.0,0.044052229523588664,0.0042325141887964,0.11824259236043642,0.2930872570585111,244
-Linear Reg.,Logistic Regr.,0.95,0.9836065573770492,0.30891916583272205,0.08765249652827344,1.0,1.0,0.044052229523588664,0.0008081901182391807,0.11824259236043642,0.2930872570585111,244
+LGBM,LGBM,0.9,0.09795918367346938,0.26979767912769265,0.1821217753924097,1.0,1.0,0.09243594786866559,0.040494673522359054,0.034931083457801146,0.3811385489487934,245
+LGBM,LGBM,0.95,0.30612244897959184,0.3214837633807111,0.1821217753924097,1.0,1.0,0.09243594786866559,0.025920252504384952,0.034931083457801146,0.3811385489487934,245
+LGBM,Logistic Regr.,0.9,0.30612244897959184,0.25780889388055256,0.1481921276548859,1.0,1.0,0.07187715697817153,0.024546744165995487,0.06294768349694302,0.35849335183083353,245
+LGBM,Logistic Regr.,0.95,0.563265306122449,0.30719824464654294,0.1481921276548859,1.0,1.0,0.07187715697817153,0.012953227730808654,0.06294768349694302,0.35849335183083353,245
+Linear Reg.,LGBM,0.9,0.10612244897959183,0.2695747491766244,0.18019285630080534,1.0,1.0,0.09421113740884988,0.04089415485221311,0.03462367597552903,0.37388485920180015,245
+Linear Reg.,LGBM,0.95,0.2979591836734694,0.32121812595984284,0.18019285630080534,1.0,1.0,0.09421113740884988,0.026079753922994376,0.03462367597552903,0.37388485920180015,245
+Linear Reg.,Logistic Regr.,0.9,0.8857142857142857,0.2592552019315289,0.08773320288603256,1.0,1.0,0.044089226784792754,0.004228149001636824,0.11817382692543607,0.2931817832302881,245
+Linear Reg.,Logistic Regr.,0.95,0.9836734693877551,0.30892162698526066,0.08773320288603256,1.0,1.0,0.044089226784792754,0.0008049142525428561,0.11817382692543607,0.2931817832302881,245

results/irm/irm_apo_sensitivity_metadata.csv

@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version,Sensitivity Errors
-0.10.dev0,irm_apo_sensitivity.py,2025-02-04 00:55:57,19823.67243719101,3.12.8,0
+0.10.dev0,irm_apo_sensitivity.py,2025-02-04 19:14:02,19864.97425556183,3.12.8,0

results/irm/irm_ate_coverage.csv

@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
 Lasso,Logistic Regression,0.9,0.875,0.467771360497192,0.12336884150536215,1000
 Lasso,Logistic Regression,0.95,0.935,0.5573839547492131,0.12336884150536215,1000
-Lasso,Random Forest,0.9,0.909,0.5986699126576687,0.1437194448121057,1000
-Lasso,Random Forest,0.95,0.958,0.7133591999985225,0.1437194448121057,1000
-Random Forest,Logistic Regression,0.9,0.8,0.5165274317458133,0.14990700956657027,1000
-Random Forest,Logistic Regression,0.95,0.883,0.6154803969548793,0.14990700956657027,1000
-Random Forest,Random Forest,0.9,0.891,0.6264098177762909,0.1516133190457161,1000
-Random Forest,Random Forest,0.95,0.952,0.7464133356834249,0.1516133190457161,1000
+Lasso,Random Forest,0.9,0.912,0.6033525996000427,0.1470798884283924,1000
+Lasso,Random Forest,0.95,0.961,0.7189389656430433,0.1470798884283924,1000
+Random Forest,Logistic Regression,0.9,0.796,0.5170183758598037,0.14999135577981693,1000
+Random Forest,Logistic Regression,0.95,0.879,0.6160653929484903,0.14999135577981693,1000
+Random Forest,Random Forest,0.9,0.898,0.6346634640451655,0.1547114295252091,1000
+Random Forest,Random Forest,0.95,0.954,0.7562481618120631,0.1547114295252091,1000

results/irm/irm_ate_coverage_metadata.csv

@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.10.dev0,irm_ate_coverage.py,2025-02-03 20:25:20,3578.0215225219727,3.12.8
+0.10.dev0,irm_ate_coverage.py,2025-02-04 14:43:01,3590.5973885059357,3.12.8

results/irm/irm_ate_sensitivity.csv

@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,Coverage (Lower),Coverage (Upper),RV,RVa,Bias (Lower),Bias (Upper),repetition
-LGBM,LGBM,0.9,0.112,0.266748233354866,0.17891290135375168,0.962,1.0,0.12379347892727971,0.05409589192160397,0.04254708028278409,0.32210978560617337,500
-LGBM,LGBM,0.95,0.318,0.31785012462427936,0.17891290135375168,0.998,1.0,0.12379347892727971,0.03441021667548556,0.04254708028278409,0.32210978560617337,500
-LGBM,Logistic Regr.,0.9,0.292,0.2577778025822409,0.14922926552528684,1.0,1.0,0.10066571951295798,0.03493291437943745,0.029012990398602386,0.2979424530565633,500
-LGBM,Logistic Regr.,0.95,0.548,0.30716119707955875,0.14922926552528684,1.0,1.0,0.10066571951295798,0.01869752301454861,0.029012990398602386,0.2979424530565633,500
-Linear Reg.,LGBM,0.9,0.122,0.2675665174758639,0.17873104426193565,0.964,1.0,0.12647219547900976,0.05512739569620471,0.04513946154555041,0.31857328180879246,500
-Linear Reg.,LGBM,0.95,0.314,0.31882517029399604,0.17873104426193565,0.998,1.0,0.12647219547900976,0.035017588858111126,0.04513946154555041,0.31857328180879246,500
-Linear Reg.,Logistic Regr.,0.9,0.86,0.2592281409673473,0.08970251629543106,1.0,1.0,0.06300567732617765,0.006719868195974334,0.05720312141493262,0.23496869651774063,500
-Linear Reg.,Logistic Regr.,0.95,0.974,0.30888938185760084,0.08970251629543106,1.0,1.0,0.06300567732617765,0.0014945204694376396,0.05720312141493262,0.23496869651774063,500
+LGBM,LGBM,0.9,0.124,0.26677505130115525,0.1765053922782123,0.976,1.0,0.12228979172211582,0.052362889318383975,0.04091552128481434,0.3196297552079361,250
+LGBM,LGBM,0.95,0.344,0.31788208017826,0.1765053922782123,1.0,1.0,0.12228979172211582,0.032810864641097386,0.04091552128481434,0.3196297552079361,250
+LGBM,Logistic Regr.,0.9,0.304,0.2579277291971309,0.14752449816798544,1.0,1.0,0.09953613548630397,0.03393799918544193,0.028764647084079123,0.29629144306647,250
+LGBM,Logistic Regr.,0.95,0.56,0.3073398456600121,0.14752449816798544,1.0,1.0,0.09953613548630397,0.017771194883930825,0.028764647084079123,0.29629144306647,250
+Linear Reg.,LGBM,0.9,0.128,0.26773478876971546,0.17729378162308507,0.972,1.0,0.12555203747310065,0.0541289777049747,0.04449232158924936,0.3171219058204927,250
+Linear Reg.,LGBM,0.95,0.312,0.3190256779076688,0.17729378162308507,0.996,1.0,0.12555203747310065,0.03412475848766324,0.04449232158924936,0.3171219058204927,250
+Linear Reg.,Logistic Regr.,0.9,0.884,0.25926273338823186,0.0876812649368125,1.0,1.0,0.06165194867300403,0.005960209905468325,0.05893348758391341,0.23285106977109127,250
+Linear Reg.,Logistic Regr.,0.95,0.984,0.3089306012694445,0.0876812649368125,1.0,1.0,0.06165194867300403,0.0011440372027301212,0.05893348758391341,0.23285106977109127,250

results/irm/irm_ate_sensitivity_metadata.csv

@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.10.dev0,irm_ate_sensitivity.py,2025-02-03 21:20:41,6893.791319608688,3.12.8
+0.10.dev0,irm_ate_sensitivity.py,2025-02-04 14:40:22,3430.5844337940216,3.12.8