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

Author: github-actions

results/irm/pq_coverage_metadata.csv

@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.10.dev0,pq_coverage.py,2025-01-08 17:13:20,17871.711226463318,3.12.8
+0.10.dev0,pq_coverage.py,2025-05-22 16:20:49,17287.969739675522,3.12.10

results/irm/pq_coverage_pq0.csv

@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-LGBM,LGBM,0.9,0.8838461538461538,0.5804011224570385,0.1489863706604989,100
-LGBM,LGBM,0.95,0.9353846153846154,0.6915905938151775,0.1489863706604989,100
-LGBM,Logistic Regression,0.9,0.8123076923076923,0.3860909559387072,0.11389794833419535,100
-LGBM,Logistic Regression,0.95,0.8876923076923078,0.46005574964077484,0.11389794833419535,100
-Logistic Regression,LGBM,0.9,0.8861538461538462,0.5879335180942487,0.1508479802166077,100
-Logistic Regression,LGBM,0.95,0.9423076923076923,0.7005659968080872,0.1508479802166077,100
-Logistic Regression,Logistic Regression,0.9,0.8246153846153846,0.3895072188527442,0.1120574898221174,100
-Logistic Regression,Logistic Regression,0.95,0.9046153846153847,0.4641264779800753,0.1120574898221174,100
+LGBM,LGBM,0.9,0.8823076923076922,0.5804011224570385,0.14917558900311645,100
+LGBM,LGBM,0.95,0.9338461538461539,0.6915905938151775,0.14917558900311645,100
+LGBM,Logistic Regression,0.9,0.8115384615384617,0.38610406439934963,0.11426502373246265,100
+LGBM,Logistic Regression,0.95,0.8869230769230769,0.4600713693350327,0.11426502373246265,100
+Logistic Regression,LGBM,0.9,0.8869230769230769,0.5879335180942487,0.15107204460433907,100
+Logistic Regression,LGBM,0.95,0.9415384615384617,0.7005659968080872,0.15107204460433907,100
+Logistic Regression,Logistic Regression,0.9,0.8223076923076923,0.3894908707564202,0.11249469872415391,100
+Logistic Regression,Logistic Regression,0.95,0.9015384615384616,0.4641069980218067,0.11249469872415391,100

results/irm/pq_coverage_pq1.csv

@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-LGBM,LGBM,0.9,0.9138461538461539,0.2504138111093655,0.058644803131633845,100
-LGBM,LGBM,0.95,0.9607692307692308,0.298386460025268,0.058644803131633845,100
-LGBM,Logistic Regression,0.9,0.9130769230769231,0.2294853436068611,0.05383096701300778,100
-LGBM,Logistic Regression,0.95,0.9623076923076923,0.2734486528645486,0.05383096701300778,100
-Logistic Regression,LGBM,0.9,0.916923076923077,0.25410039964172587,0.059305556876141904,100
-Logistic Regression,LGBM,0.95,0.9615384615384616,0.3027793012063014,0.059305556876141904,100
-Logistic Regression,Logistic Regression,0.9,0.8976923076923078,0.23093595343208725,0.057241427868032047,100
-Logistic Regression,Logistic Regression,0.95,0.9546153846153846,0.27517716108344265,0.057241427868032047,100
+LGBM,LGBM,0.9,0.9153846153846155,0.2504138111093655,0.058637832346116046,100
+LGBM,LGBM,0.95,0.9623076923076923,0.298386460025268,0.058637832346116046,100
+LGBM,Logistic Regression,0.9,0.9138461538461539,0.2294851617480571,0.053811638122637194,100
+LGBM,Logistic Regression,0.95,0.9623076923076923,0.273448436166418,0.053811638122637194,100
+Logistic Regression,LGBM,0.9,0.9192307692307692,0.25410039964172587,0.059350250451121786,100
+Logistic Regression,LGBM,0.95,0.9607692307692308,0.3027793012063014,0.059350250451121786,100
+Logistic Regression,Logistic Regression,0.9,0.8976923076923078,0.23093621538720735,0.05722710381019568,100
+Logistic Regression,Logistic Regression,0.95,0.9538461538461539,0.2751774732222205,0.05722710381019568,100

results/irm/pq_coverage_qte.csv

@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
-LGBM,LGBM,0.9,0.8815384615384616,0.6176207568284253,0.15515498246785267,0.85,0.9336715877443045,100
-LGBM,LGBM,0.95,0.94,0.7359405236146267,0.15515498246785267,0.91,1.0306538899948843,100
-LGBM,Logistic Regression,0.9,0.826923076923077,0.4257337159670842,0.122640423715187,0.78,0.6459408206266708,100
-LGBM,Logistic Regression,0.95,0.9092307692307692,0.5072930117474264,0.122640423715187,0.84,0.7141895123082023,100
-Logistic Regression,LGBM,0.9,0.8969230769230769,0.6286198118927271,0.15916890224887578,0.87,0.9308233463178209,100
-Logistic Regression,LGBM,0.95,0.946923076923077,0.7490467060960181,0.15916890224887578,0.92,1.029300136308572,100
-Logistic Regression,Logistic Regression,0.9,0.8407692307692308,0.43448201352405663,0.12418740801387926,0.81,0.6474698211016049,100
-Logistic Regression,Logistic Regression,0.95,0.9123076923076923,0.5177172512400822,0.12418740801387926,0.85,0.719895714650183,100
+LGBM,LGBM,0.9,0.8823076923076922,0.6176207568284253,0.15519922876616388,0.84,0.9336715877443045,100
+LGBM,LGBM,0.95,0.9392307692307692,0.7359405236146267,0.15519922876616388,0.91,1.0306538899948843,100
+LGBM,Logistic Regression,0.9,0.8261538461538461,0.4257458252181111,0.1226898281791693,0.78,0.6459797086090959,100
+LGBM,Logistic Regression,0.95,0.9107692307692308,0.5073074408099907,0.1226898281791693,0.84,0.7142375039945987,100
+Logistic Regression,LGBM,0.9,0.8930769230769231,0.6286198118927271,0.1592095091097193,0.87,0.9308233463178209,100
+Logistic Regression,LGBM,0.95,0.9476923076923077,0.7490467060960181,0.1592095091097193,0.92,1.029300136308572,100
+Logistic Regression,Logistic Regression,0.9,0.8415384615384616,0.43446715078562453,0.12422823365772839,0.8,0.6474624649583857,100
+Logistic Regression,Logistic Regression,0.95,0.9123076923076923,0.5176995411949078,0.12422823365772839,0.86,0.719846486999326,100