Merge branch 'xKDR:main' into main

xKDR · Oct 21, 2024 · 03af97f · 03af97f
2 parents 8bfbbfb + 6488b11
commit 03af97f
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Showing 6 changed files with 16 additions and 15 deletions.
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
@@ -17,9 +17,9 @@ jobs:
             - uses: actions/checkout@v2
             - uses: julia-actions/setup-julia@latest
               with:
-                version: '1.7.2'
+                version: '1.7.3'
                 arch: x64
             - name: Install test dependencies
               run: julia --project=test/ -e 'using Pkg; Pkg.instantiate()'
             - name: Run tests
-              run: julia --project=. -e 'using Pkg; Pkg.test()'
+              run: julia --project=. -e 'using Pkg; Pkg.test()'
diff --git a/Project.toml b/Project.toml
@@ -21,14 +21,15 @@ Turing = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
 [compat]
 DataFrames = "1"
 Distributions = "0.25"
-Documenter = "0.27"
+Documenter = "0.27, 1"
 GLM = "1"
+HypothesisTests = "0.11"
 NLSolversBase = "7"
 Optim = "1"
 StatsAPI = "1"
-StatsBase = "0.33"
+StatsBase = "0.33, 0.34"
 StatsModels = "0.6"
-Turing = "0.23.2, 0.24"
+Turing = "0.23.2, 0.24, 0.32, 0.34"
 julia = "1"
 
 [extras]

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