Updated tests to use standard deviation

xKDR · May 6, 2024 · f237be8 · f237be8
1 parent 40894f0
commit f237be8
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Showing 4 changed files with 10 additions and 10 deletions.
diff --git a/test/numerical/bayesian/LinearRegression.jl b/test/numerical/bayesian/LinearRegression.jl
@@ -11,13 +11,13 @@ tests = [
 for (prior, test_mean) in tests
     CRRao.set_rng(StableRNG(123))
     model = fit(@formula(MPG ~ HP + WT + Gear), mtcars, LinearRegression(), prior)
-
-    @test mean(predict(model, mtcars)) ≈ test_mean
+    prediction = predict(model, mtcars)
+    @test mean(prediction) - 2 * std(prediction) <= test_mean && test_mean <= mean(prediction) + 2 * std(prediction)
 end
 
 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)
-
-@test mean(predict(model, mtcars)) ≈ gauss_test
+prediction = predict(model, mtcars)
+@test mean(prediction) - 2 * std(prediction) <= gauss_test && gauss_test <= mean(prediction) + 2 * std(prediction)
diff --git a/test/numerical/bayesian/LogisticRegression.jl b/test/numerical/bayesian/LogisticRegression.jl
@@ -52,7 +52,7 @@ for (prior, prior_testcases) in tests
     for (link, test_mean) in prior_testcases
         CRRao.set_rng(StableRNG(123))
         model = fit(@formula(Vote ~ Age + Race + Income + Educate), turnout, LogisticRegression(), link, prior)
-
-        @test mean(predict(model, turnout)) ≈ test_mean
+        prediction = predict(model, turnout)
+        @test mean(prediction) - 2 * std(prediction) <= test_mean && test_mean <= mean(prediction) + 2 * std(prediction)
     end
 end
diff --git a/test/numerical/bayesian/NegBinomialRegression.jl b/test/numerical/bayesian/NegBinomialRegression.jl
@@ -11,6 +11,6 @@ tests = [
 for (prior, test_mean) in tests
     CRRao.set_rng(StableRNG(123))
     model = fit(@formula(Num ~ Target + Coop + NCost), sanction, NegBinomRegression(), prior)
-
-    @test mean(predict(model, sanction)) ≈ test_mean
+    prediction = predict(model, sanction)
+    @test mean(prediction) - 2 * std(prediction) <= test_mean && test_mean <= mean(prediction) + 2 * std(prediction)
 end
diff --git a/test/numerical/bayesian/PoissonRegression.jl b/test/numerical/bayesian/PoissonRegression.jl
@@ -11,6 +11,6 @@ tests = [
 for (prior, test_mean) in tests
     CRRao.set_rng(StableRNG(123))
     model = fit(@formula(Num ~ Target + Coop + NCost), sanction, PoissonRegression(), prior)
-
-    @test mean(predict(model, sanction)) ≈ test_mean
+    prediction = predict(model, sanction)
+    @test mean(prediction) - 2 * std(prediction) <= test_mean && test_mean <= mean(prediction) + 2 * std(prediction)
 end