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
-0.9.0,pq_coverage.py,2024-09-09 12:24:40,18061.192512512207,3.12.5
+0.10.dev0,pq_coverage.py,2025-01-08 17:13:20,17871.711226463318,3.12.8

results/irm/pq_coverage_pq0.csv

@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-LGBM,LGBM,0.9,0.8823076923076922,0.5804011224570385,0.1491025005152581,100
-LGBM,LGBM,0.95,0.9346153846153846,0.6915905938151775,0.1491025005152581,100
-LGBM,Logistic Regression,0.9,0.8115384615384617,0.3861407256651673,0.11416614656762226,100
-LGBM,Logistic Regression,0.95,0.8861538461538462,0.46011505392766316,0.11416614656762226,100
-Logistic Regression,LGBM,0.9,0.8853846153846153,0.5879335180942484,0.15100690944933073,100
-Logistic Regression,LGBM,0.95,0.9415384615384617,0.7005659968080868,0.15100690944933073,100
-Logistic Regression,Logistic Regression,0.9,0.8223076923076923,0.38942866423036987,0.1123937956401062,100
-Logistic Regression,Logistic Regression,0.95,0.9015384615384616,0.46403287437416774,0.1123937956401062,100
+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

results/irm/pq_coverage_pq1.csv

@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-LGBM,LGBM,0.9,0.9130769230769231,0.2504138111093655,0.05865662571787472,100
-LGBM,LGBM,0.95,0.9623076923076923,0.298386460025268,0.05865662571787472,100
-LGBM,Logistic Regression,0.9,0.91,0.22948465548607,0.05375633654188718,100
-LGBM,Logistic Regression,0.95,0.9615384615384616,0.2734478329180528,0.05375633654188718,100
-Logistic Regression,LGBM,0.9,0.9192307692307692,0.25410039964172587,0.059363532936649595,100
-Logistic Regression,LGBM,0.95,0.9607692307692308,0.3027793012063014,0.059363532936649595,100
-Logistic Regression,Logistic Regression,0.9,0.8984615384615385,0.23093353063439134,0.057191896173723104,100
-Logistic Regression,Logistic Regression,0.95,0.9553846153846153,0.27517427414192513,0.057191896173723104,100
+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

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,0.9,0.8815384615384616,0.6176207568284253,0.15504772624658503,0.85,0.9336715877443045,100
-LGBM,LGBM,0.95,0.9407692307692308,0.7359405236146267,0.15504772624658503,0.91,1.0306538899948843,100
-LGBM,Logistic Regression,0.9,0.83,0.4257824194261344,0.12245088179297632,0.78,0.6460154145368233,100
-LGBM,Logistic Regression,0.95,0.9084615384615385,0.5073510454983309,0.12245088179297632,0.84,0.714250944722706,100
-Logistic Regression,LGBM,0.9,0.8961538461538461,0.6286198118927269,0.15900405481444213,0.87,0.9308233463178206,100
-Logistic Regression,LGBM,0.95,0.9484615384615386,0.7490467060960178,0.15900405481444213,0.92,1.0293001363085716,100
-Logistic Regression,Logistic Regression,0.9,0.8430769230769231,0.4344065634613077,0.12399216449911891,0.81,0.647334882587494,100
-Logistic Regression,Logistic Regression,0.95,0.9115384615384616,0.5176273469451368,0.12399216449911891,0.86,0.7197477669291079,100
+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