stat/distmv: Add ScoreInput function for the Normal distribution
MODIFY
stat/distmv/normal_test.go
stat/distmv/normal_test.go
@@ -9,6 +9,7 @@ import (
"math/rand"
"testing"
+ "gonum.org/v1/gonum/diff/fd"
"gonum.org/v1/gonum/floats"
"gonum.org/v1/gonum/mat"
"gonum.org/v1/gonum/stat"
@@ -536,3 +537,37 @@ func TestMarginalSingle(t *testing.T) {
}
}
}
+
+func TestNormalScoreInput(t *testing.T) {
+ for cas, test := range []struct {
+ mu []float64
+ sigma *mat.SymDense
+ x []float64
+ }{
+ {
+ mu: []float64{2, 3, 4},
+ sigma: mat.NewSymDense(3, []float64{2, 0.5, 3, 0.5, 1, 0.6, 3, 0.6, 10}),
+ x: []float64{1, 3.1, -2},
+ },
+ {
+ mu: []float64{2, 3, 4, 5},
+ sigma: mat.NewSymDense(4, []float64{2, 0.5, 3, 0.1, 0.5, 1, 0.6, 0.2, 3, 0.6, 10, 0.3, 0.1, 0.2, 0.3, 3}),
+ x: []float64{1, 3.1, -2, 5},
+ },
+ } {
+ normal, ok := NewNormal(test.mu, test.sigma, nil)
+ if !ok {
+ t.Fatalf("Bad test, covariance matrix not positive definite")
+ }
+ x := make([]float64, len(test.x))
+ copy(x, test.x)
+ score := normal.ScoreInput(nil, x)
+ if !floats.Equal(x, test.x) {
+ t.Errorf("x modified during call to ScoreInput")
+ }
+ scoreFD := fd.Gradient(nil, normal.LogProb, x, nil)
+ if !floats.EqualApprox(score, scoreFD, 1e-4) {
+ t.Errorf("Case %d: derivative mismatch. Got %v, want %v", cas, score, scoreFD)
+ }
+ }
+}

stat/distmv: Add ScoreInput function for the Normal distribution