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

Author: github-actions

results/irm/cvar_coverage_metadata.csv

@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.10.dev0,cvar_coverage.py,2025-01-08 16:49:01,16412.1168384552,3.12.8
+0.10.dev0,cvar_coverage.py,2025-05-22 15:47:04,15261.781089544296,3.12.10

results/irm/cvar_coverage_pq0.csv

@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-LGBM,LGBM,0.9,0.8884615384615384,0.5699689541680535,0.13934954721406115,100
-LGBM,LGBM,0.95,0.9461538461538461,0.6791598985897508,0.13934954721406115,100
-LGBM,Logistic Regression,0.9,0.8192307692307692,0.4060217020758364,0.11848308187809455,100
-LGBM,Logistic Regression,0.95,0.8892307692307692,0.48380469846741503,0.11848308187809455,100
-Linear,LGBM,0.9,0.7692307692307692,0.5801661718639771,0.1751137266106609,100
-Linear,LGBM,0.95,0.8615384615384616,0.691310632915921,0.1751137266106609,100
-Linear,Logistic Regression,0.9,0.6892307692307692,0.42946981193983413,0.1545041280672664,100
-Linear,Logistic Regression,0.95,0.7776923076923077,0.5117448446822186,0.1545041280672664,100
+LGBM,LGBM,0.9,0.8892307692307692,0.5699689541680535,0.13916120902511853,100
+LGBM,LGBM,0.95,0.9461538461538461,0.6791598985897508,0.13916120902511853,100
+LGBM,Logistic Regression,0.9,0.8207692307692308,0.4060171336908242,0.11838313391016886,100
+LGBM,Logistic Regression,0.95,0.8907692307692308,0.4837992549009209,0.11838313391016886,100
+Linear,LGBM,0.9,0.7707692307692308,0.5801661718639771,0.1746635044255932,100
+Linear,LGBM,0.95,0.8630769230769231,0.691310632915921,0.1746635044255932,100
+Linear,Logistic Regression,0.9,0.69,0.4294697114538,0.1539651338207486,100
+Linear,Logistic Regression,0.95,0.7792307692307692,0.5117447249457237,0.1539651338207486,100

results/irm/cvar_coverage_pq1.csv

@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-LGBM,LGBM,0.9,0.9323076923076923,0.1908311409902022,0.04358145932430658,100
-LGBM,LGBM,0.95,0.9776923076923077,0.22738932956769187,0.04358145932430658,100
-LGBM,Logistic Regression,0.9,0.9130769230769231,0.17764550716816235,0.04414608757632295,100
-LGBM,Logistic Regression,0.95,0.963076923076923,0.21167767779450106,0.04414608757632295,100
-Linear,LGBM,0.9,0.9292307692307692,0.21584587388672186,0.047457925834839765,100
-Linear,LGBM,0.95,0.9769230769230769,0.25719622226423833,0.047457925834839765,100
-Linear,Logistic Regression,0.9,0.8823076923076922,0.19342205011642188,0.0494625033437771,100
-Linear,Logistic Regression,0.95,0.9415384615384617,0.2304765882096771,0.0494625033437771,100
+LGBM,LGBM,0.9,0.9323076923076923,0.1908311409902022,0.04341246693737058,100
+LGBM,LGBM,0.95,0.9792307692307692,0.22738932956769187,0.04341246693737058,100
+LGBM,Logistic Regression,0.9,0.9130769230769231,0.1776451248637835,0.04403267398281018,100
+LGBM,Logistic Regression,0.95,0.963076923076923,0.21167722225073635,0.04403267398281018,100
+Linear,LGBM,0.9,0.9307692307692308,0.21584587388672186,0.047576051617349686,100
+Linear,LGBM,0.95,0.9776923076923077,0.25719622226423833,0.047576051617349686,100
+Linear,Logistic Regression,0.9,0.8884615384615384,0.1934218436107483,0.04906705213284509,100
+Linear,Logistic Regression,0.95,0.943076923076923,0.23047634214298993,0.04906705213284509,100

results/irm/cvar_coverage_qte.csv

@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
-LGBM,LGBM,0.9,0.9038461538461539,0.5818966962059838,0.1435944755709475,0.88,0.7055777033989438,100
-LGBM,LGBM,0.95,0.9492307692307692,0.693372679853793,0.1435944755709475,0.94,0.8113769406399532,100
-LGBM,Logistic Regression,0.9,0.81,0.41716340917968886,0.12258144778601979,0.78,0.5062698827872832,100
-LGBM,Logistic Regression,0.95,0.8738461538461538,0.49708086133810014,0.12258144778601979,0.86,0.5835143322993298,100
-Linear,LGBM,0.9,0.8023076923076923,0.6065907561805581,0.1790914579109802,0.8,0.7182897195756133,100
-Linear,LGBM,0.95,0.8653846153846153,0.7227974671960807,0.1790914579109802,0.85,0.8301176550726784,100
-Linear,Logistic Regression,0.9,0.713076923076923,0.4541725983633358,0.15175636482362434,0.71,0.5341780882458428,100
-Linear,Logistic Regression,0.95,0.8146153846153846,0.541180030229751,0.15175636482362434,0.8,0.6185746229300051,100
+LGBM,LGBM,0.9,0.9007692307692308,0.5818966962059838,0.14389616733672375,0.88,0.7055777033989438,100
+LGBM,LGBM,0.95,0.9492307692307692,0.693372679853793,0.14389616733672375,0.95,0.8113769406399532,100
+LGBM,Logistic Regression,0.9,0.81,0.41715844354328135,0.12275759703405408,0.78,0.5062794648957274,100
+LGBM,Logistic Regression,0.95,0.8692307692307693,0.49707494441737266,0.12275759703405408,0.86,0.5835121707560351,100
+Linear,LGBM,0.9,0.8007692307692308,0.6065907561805581,0.1798354817301676,0.8,0.7182897195756133,100
+Linear,LGBM,0.95,0.8638461538461538,0.7227974671960807,0.1798354817301676,0.85,0.8301176550726784,100
+Linear,Logistic Regression,0.9,0.7084615384615384,0.45417244635105875,0.15263121995044057,0.69,0.5341807534621331,100
+Linear,Logistic Regression,0.95,0.8123076923076923,0.5411798490959508,0.15263121995044057,0.8,0.6185753871641957,100