Merge c075476 into da3b70d

.travis.yml

@@ -6,7 +6,7 @@ os:
 
 julia:
   - 1.0
-  - 1.3
+  - 1
   - nightly
 
 matrix:

Project.toml

@@ -22,7 +22,8 @@ julia = "1"
 
 [extras]
 DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
+StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["DelimitedFiles", "Test"]
+test = ["DelimitedFiles", "StableRNGs", "Test"]

src/HypothesisTests.jl

@@ -98,7 +98,8 @@ function check_level(level::Float64)
 end
 
 # Pretty-print
-function Base.show(io::IO, test::T) where T<:HypothesisTest
+function Base.show(_io::IO, test::T) where T<:HypothesisTest
+    io = IOContext(_io, :compact=>get(_io, :compact, true))
     println(io, testname(test))
     println(io, repeat("-", length(testname(test))))
 

test/f.jl

@@ -1,22 +1,23 @@
 using HypothesisTests, Test
 using HypothesisTests: default_tail
+using StableRNGs
 
 @testset "F-tests" begin
     @testset "Basic variance F-test" begin
-        Random.seed!(12)
-        y1_h0 = 4 .+ randn(500)
-        y2_h0 = 4 .+ randn(400)
+        rng = StableRNG(12)
+        y1_h0 = 4 .+ randn(rng, 500)
+        y2_h0 = 4 .+ randn(rng, 400)
 
         t = VarianceFTest(y1_h0, y2_h0)
 
         @test t.n_x == 500
         @test t.n_y == 400
         @test t.df_x == 499
         @test t.df_y == 399
-        @test t.F ≈ 0.974693 rtol=1e-5
-        @test pvalue(t) ≈ 0.784563 rtol=1e-5
-        @test pvalue(t, tail=:left) ≈ 0.392281 rtol=1e-5
-        @test pvalue(t, tail=:right) ≈ 0.607718 rtol=1e-5
+        @test t.F                    ≈ 0.859582  rtol=1e-5
+        @test pvalue(t)              ≈ 0.109714  rtol=1e-5
+        @test pvalue(t, tail=:left)  ≈ 0.0548572 rtol=1e-5
+        @test pvalue(t, tail=:right) ≈ 0.945143  rtol=1e-5
         @test default_tail(t) == :both
 
         t = VarianceFTest(y2_h0, y1_h0)
@@ -25,22 +26,22 @@ using HypothesisTests: default_tail
         @test t.n_y == 500
         @test t.df_x == 399
         @test t.df_y == 499
-        @test t.F ≈ 1.025963 rtol=1e-5
-        @test pvalue(t) ≈ 0.784563 rtol=1e-5
-        @test pvalue(t, tail=:right) ≈ 0.392281 rtol=1e-5
-        @test pvalue(t, tail=:left) ≈ 0.607718 rtol=1e-5
+        @test t.F                    ≈ 1.163355  rtol=1e-5
+        @test pvalue(t)              ≈ 0.109714  rtol=1e-5
+        @test pvalue(t, tail=:right) ≈ 0.0548572 rtol=1e-5
+        @test pvalue(t, tail=:left)  ≈ 0.945143 rtol=1e-5
         @test default_tail(t) == :both
 
-        y1_h1 = 0.7*randn(200)
-        y2_h1 = 1.3*randn(120)
+        y1_h1 = 0.7*randn(rng, 200)
+        y2_h1 = 1.3*randn(rng, 120)
 
         t = VarianceFTest(y1_h1, y2_h1)
 
         @test t.n_x == 200
         @test t.n_y == 120
         @test t.df_x == 199
         @test t.df_y == 119
-        @test t.F ≈ 0.367547 rtol=1e-5
+        @test t.F ≈ 0.264161 rtol=1e-5
         @test pvalue(t) < 1e-8
         @test default_tail(t) == :both
         @test pvalue(t, tail=:left) < 1e-8

test/show.jl

@@ -5,6 +5,7 @@ using HypothesisTests, Test
 d = [[762,484] [327,239] [468,477]]
 m = PowerDivergenceTest(d)
 
+if VERSION < v"1.4"
 @test sprint(show, m, context=:compact => true) ==
     """
     Pearson's Chi-square Test
@@ -51,6 +52,54 @@ m = PowerDivergenceTest(d)
         residuals:          [0.0, -1.11803, 1.11803]
         std. residuals:     [0.0, -1.36931, 1.36931]
     """
+else
+@test sprint(show, m, context=:compact => true) ==
+    """
+    Pearson's Chi-square Test
+    -------------------------
+    Population details:
+        parameter of interest:   Multinomial Probabilities
+        value under h_0:         [0.255231, 0.19671, 0.11594, 0.0893561, 0.193574, 0.14919]
+        point estimate:          [0.276387, 0.175553, 0.118607, 0.0866884, 0.16975, 0.173014]
+        95% confidence interval: [(0.2545, 0.2994), (0.1573, 0.1955), (0.1033, 0.1358), (0.0736, 0.1019), (0.1517, 0.1894), (0.1548, 0.1928)]
+
+    Test summary:
+        outcome with 95% confidence: reject h_0
+        one-sided p-value:           <1e-6
+
+    Details:
+        Sample size:        2757
+        statistic:          30.070149095754687
+        degrees of freedom: 2
+        residuals:          [2.19886, -2.50467, 0.41137, -0.468583, -2.84324, 3.23867]
+        std. residuals:     [4.50205, -4.50205, 0.699452, -0.699452, -5.31595, 5.31595]
+    """
+
+d = [ 20, 15, 25 ]
+m = PowerDivergenceTest(d)
+
+@test sprint(show, m, context=:compact => true) ==
+    """
+    Pearson's Chi-square Test
+    -------------------------
+    Population details:
+        parameter of interest:   Multinomial Probabilities
+        value under h_0:         [0.333333, 0.333333, 0.333333]
+        point estimate:          [0.333333, 0.25, 0.416667]
+        95% confidence interval: [(0.2167, 0.481), (0.1333, 0.3976), (0.3, 0.5643)]
+
+    Test summary:
+        outcome with 95% confidence: fail to reject h_0
+        one-sided p-value:           0.2865
+
+    Details:
+        Sample size:        60
+        statistic:          2.5
+        degrees of freedom: 2
+        residuals:          [0.0, -1.11803, 1.11803]
+        std. residuals:     [0.0, -1.36931, 1.36931]
+    """
+end
 
 # based on t.jl tests
 tst = OneSampleTTest(-5:10)

test/white.jl

@@ -221,15 +221,15 @@ e = [ 5.19346;
     Population details:
         parameter of interest:   T*R2
         value under h_0:         0
-        point estimate:          $(w_test.lm)
+        point estimate:          $(sprint(show, w_test.lm; context=:compact => true))
 
     Test summary:
         outcome with 95% confidence: fail to reject h_0
         one-sided p-value:           $(round(w_pval,digits=4))
 
     Details:
-        T*R^2 statistic:        $(w_test.lm)
-        degrees of freedom:     $(w_test.dof)
+        T*R^2 statistic:        $(sprint(show, w_test.lm  ; context=:compact => true))
+        degrees of freedom:     $(sprint(show, w_test.dof ; context=:compact => true))
         type:                   $(w_test.type)
     """