Update the test cases

xKDR · Dec 25, 2022 · 433a5d1 · 433a5d1
1 parent 88f2735
commit 433a5d1
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Showing 4 changed files with 36 additions and 36 deletions.
diff --git a/test/numerical/bayesian/LinearRegression.jl b/test/numerical/bayesian/LinearRegression.jl
@@ -1,11 +1,11 @@
 mtcars = dataset("datasets", "mtcars")
 
 tests = [
-    (Prior_Ridge(), 20.094329014886135),
-    (Prior_Laplace(), 20.070803242904567),
-    (Prior_Cauchy(), 20.089299279637608),
-    (Prior_TDist(), 20.07675037883895),
-    (Prior_HorseShoe(), 20.08147629414915),
+    (Prior_Ridge(), 20.080877893580514),
+    (Prior_Laplace(), 20.070783434589128),
+    (Prior_Cauchy(), 20.019759144845644),
+    (Prior_TDist(), 20.042614331921428),
+    (Prior_HorseShoe(), 20.042984550677183),
 ]
 
 for (prior, test_mean) in tests
@@ -15,7 +15,7 @@ for (prior, test_mean) in tests
     @test mean(predict(model, mtcars)) ≈ test_mean
 end
 
-gauss_test = 20.077725307634
+gauss_test = 20.0796026428345
 
 CRRao.set_rng(StableRNG(123))
 model = fit(@formula(MPG ~ HP + WT + Gear), mtcars, LinearRegression(), Prior_Gauss(), 30.0, [0.0,-3.0,1.0], 1000)

diff --git a/test/numerical/bayesian/LogisticRegression.jl b/test/numerical/bayesian/LogisticRegression.jl
@@ -4,46 +4,46 @@ tests = [
     (
         Prior_Ridge(),
         (
-            (Logit(), 0.7726301574939893),
-            (Probit(), 0.7718991855077517),
-            (Cloglog(), 0.7729607868936296),
-            (Cauchit(), 0.773088648259103)
+            (Logit(), 0.7690822208626806),
+            (Probit(), 0.7685999218881091),
+            (Cloglog(), 0.7751111243871245),
+            (Cauchit(), 0.7730511118602764)
         )
     ),
     (
         Prior_Laplace(),
         (
-            (Logit(), 0.7721450629705013),
-            (Probit(), 0.7700924638261658),
-            (Cloglog(), 0.7725984571763792),
-            (Cauchit(), 0.7733539997964879)
+            (Logit(), 0.7718593681922629),
+            (Probit(), 0.7695587585010469),
+            (Cloglog(), 0.7714870967902365),
+            (Cauchit(), 0.7714839338283468)
         )
     ),
     (
         Prior_Cauchy(),
         (
-            (Logit(), 0.7490077946647627),
-            (Probit(), 0.7666419321169409),
-            (Cloglog(), 0.7630424969124491),
-            (Cauchit(), 0.7751462774369108)
+            (Logit(), 0.7678814727043146),
+            (Probit(), 0.764699194194744),
+            (Cloglog(), 0.7642369367775604),
+            (Cauchit(), 0.7692152829967064)
         )
     ),
     (
         Prior_TDist(),
         (
-            (Logit(), 0.5859376296718818),
-            (Probit(), 0.7612744071932722),
-            (Cloglog(), 0.7584442886274094),
-            (Cauchit(), 0.7715325526207547)
+            (Logit(), 0.588835403024102),
+            (Probit(), 0.7635642627091132),
+            (Cloglog(), 0.7609943137312546),
+            (Cauchit(), 0.772095066757767)
         )
     ),
     (
         Prior_HorseShoe(),
         (
-            (Logit(), 0.38795793121702976),
-            (Probit(), 0.4088010293870976),
-            (Cloglog(), 0.7662231188565767),
-            (Cauchit(), 0.7685459396568979)
+            (Logit(), 0.38683395333332327),
+            (Probit(), 0.38253233489484173),
+            (Cloglog(), 0.7667553778881738),
+            (Cauchit(), 0.7706755564626601)
         )
     ),
 ]

diff --git a/test/numerical/bayesian/NegBinomialRegression.jl b/test/numerical/bayesian/NegBinomialRegression.jl
@@ -1,11 +1,11 @@
 sanction = dataset("Zelig", "sanction")
 
 tests = [
-    (Prior_Ridge(), 6.89333113986786),
-    (Prior_Laplace(), 6.868506051646364),
-    (Prior_Cauchy(), 6.871750107984425),
-    (Prior_TDist(), 6.871687824045264),
-    (Prior_HorseShoe(), 6.512395375168992),
+    (Prior_Ridge(), 6.8753100988051274),
+    (Prior_Laplace(), 6.908332048475347),
+    (Prior_Cauchy(), 6.9829255933233645),
+    (Prior_TDist(), 6.915515248823249),
+    (Prior_HorseShoe(), 6.703023191644206),
 ]
 
 for (prior, test_mean) in tests

diff --git a/test/numerical/bayesian/PoissonRegression.jl b/test/numerical/bayesian/PoissonRegression.jl
@@ -1,11 +1,11 @@
 sanction = dataset("Zelig", "sanction")
 
 tests = [
-    (Prior_Ridge(), 7.156569426585206),
-    (Prior_Laplace(), 7.147034162448096),
-    (Prior_Cauchy(), 7.160021974618625),
-    (Prior_TDist(), 7.144672898872307),
-    (Prior_HorseShoe(), 7.139133430699899),
+    (Prior_Ridge(), 7.177578002644547),
+    (Prior_Laplace(), 7.1454141602741785),
+    (Prior_Cauchy(), 7.148699646242317),
+    (Prior_TDist(), 7.165968828611132),
+    (Prior_HorseShoe(), 7.144190707091213),
 ]
 
 for (prior, test_mean) in tests