github.com/jingcheng-WU/gonum@v0.9.1-0.20210323123734-f1a2a11a8f7b/stat/distuv/inversegamma_test.go (about)

     1  // Copyright ©2018 The Gonum Authors. All rights reserved.
     2  // Use of this source code is governed by a BSD-style
     3  // license that can be found in the LICENSE file.
     4  
     5  package distuv
     6  
     7  import (
     8  	"math"
     9  	"sort"
    10  	"testing"
    11  
    12  	"golang.org/x/exp/rand"
    13  
    14  	"github.com/jingcheng-WU/gonum/floats/scalar"
    15  )
    16  
    17  func TestInverseGamma(t *testing.T) {
    18  	t.Parallel()
    19  	// Values extracted from a comparison with scipy
    20  	for _, test := range []struct {
    21  		x, alpha, want float64
    22  	}{
    23  		{0.9, 4.5, 0.050521067785046482},
    24  		{0.04, 45, 0.10550644842525572},
    25  		{20, 0.4, 0.0064691988681571536},
    26  	} {
    27  		pdf := InverseGamma{Alpha: test.alpha, Beta: 1}.Prob(test.x)
    28  		if !scalar.EqualWithinAbsOrRel(pdf, test.want, 1e-10, 1e-10) {
    29  			t.Errorf("Pdf mismatch. Got %v, want %v", pdf, test.want)
    30  		}
    31  	}
    32  	src := rand.NewSource(1)
    33  	for i, g := range []InverseGamma{
    34  		{Alpha: 5.6, Beta: 0.5, Src: src},
    35  		{Alpha: 30, Beta: 1.7, Src: src},
    36  		{Alpha: 30.2, Beta: 1.7, Src: src},
    37  	} {
    38  		testInverseGamma(t, g, i)
    39  	}
    40  }
    41  
    42  func testInverseGamma(t *testing.T, f InverseGamma, i int) {
    43  	const (
    44  		tol  = 1e-2
    45  		n    = 2e6
    46  		bins = 50
    47  	)
    48  	x := make([]float64, n)
    49  	generateSamples(x, f)
    50  	sort.Float64s(x)
    51  
    52  	testRandLogProbContinuous(t, i, 0, x, f, tol, bins)
    53  	checkMean(t, i, x, f, tol)
    54  	checkVarAndStd(t, i, x, f, 2e-2)
    55  	checkExKurtosis(t, i, x, f, 2e-1)
    56  	checkProbContinuous(t, i, x, 0, math.Inf(1), f, 1e-10)
    57  	checkQuantileCDFSurvival(t, i, x, f, 5e-2)
    58  	checkMode(t, i, x, f, 1e-2, 1e-2)
    59  
    60  	cdf0 := f.CDF(0)
    61  	if cdf0 != 0 {
    62  		t.Errorf("Expected zero CDF at 0, but got: %v", cdf0)
    63  	}
    64  	cdfNeg := f.CDF(-0.0001)
    65  	if cdfNeg != 0 {
    66  		t.Errorf("Expected zero CDF for a negative argument, but got: %v", cdfNeg)
    67  	}
    68  	surv0 := f.Survival(0)
    69  	if surv0 != 1 {
    70  		t.Errorf("Mismatch in Survival at 0. Got %v, want 1", surv0)
    71  	}
    72  	survNeg := f.Survival(-0.0001)
    73  	if survNeg != 1 {
    74  		t.Errorf("Mismatch in Survival for a negative argument. Got %v, want 1", survNeg)
    75  	}
    76  	if f.NumParameters() != 2 {
    77  		t.Errorf("Mismatch in NumParameters. Got %v, want 2", f.NumParameters())
    78  	}
    79  	pdf0 := f.Prob(0)
    80  	if pdf0 != 0 {
    81  		t.Errorf("Expected zero PDF at 0, but got: %v", pdf0)
    82  	}
    83  	pdfNeg := f.Prob(-0.0001)
    84  	if pdfNeg != 0 {
    85  		t.Errorf("Expected zero PDF for a negative argument, but got: %v", pdfNeg)
    86  	}
    87  }
    88  
    89  func TestInverseGammaLowAlpha(t *testing.T) {
    90  	t.Parallel()
    91  	f := InverseGamma{Alpha: 1, Beta: 1}
    92  	mean := f.Mean()
    93  	if !math.IsInf(mean, 1) {
    94  		t.Errorf("Expected +Inf mean for alpha <= 1, got %v", mean)
    95  	}
    96  	f = InverseGamma{Alpha: 2, Beta: 1}
    97  	stdDev := f.StdDev()
    98  	if !math.IsInf(stdDev, 1) {
    99  		t.Errorf("Expected +Inf standard deviation for alpha <= 2, got %v", stdDev)
   100  	}
   101  	variance := f.Variance()
   102  	if !math.IsInf(variance, 1) {
   103  		t.Errorf("Expected +Inf variance for alpha <= 2, got %v", variance)
   104  	}
   105  	f = InverseGamma{Alpha: 4, Beta: 1}
   106  	exKurt := f.ExKurtosis()
   107  	if !math.IsInf(exKurt, 1) {
   108  		t.Errorf("Expected +Inf excess kurtosis for alpha <= 4, got %v", exKurt)
   109  	}
   110  }