feature: add skew, covariance and variance

pkg/types/indicator.go

@@ -733,4 +733,51 @@ func Correlation(a Series, b Series, length int, method ...CorrFunc) float64 {
 	return runner(a, b, length)
 }
 
+// similar to pandas.Series.cov() function with ddof=0
+//
+// Compute covariance with Series
+func Covariance(a Series, b Series, length int) float64 {
+	if a.Length() < length {
+		length = a.Length()
+	}
+	if b.Length() < length {
+		length = b.Length()
+	}
+
+	meana := Mean(a, length)
+	meanb := Mean(b, length)
+	sum := 0.0
+	for i := 0; i < length; i++ {
+		sum += (a.Index(i) - meana) * (b.Index(i) - meanb)
+	}
+	sum /= float64(length)
+	return sum
+}
+
+func Variance(a Series, length int) float64 {
+	return Covariance(a, a, length)
+}
+
+// similar to pandas.Series.skew() function.
+//
+// Return unbiased skew over input series
+func Skew(a Series, length int) float64 {
+	if length > a.Length() {
+		length = a.Length()
+	}
+	mean := Mean(a, length)
+	sum2 := 0.0
+	sum3 := 0.0
+	for i := 0; i < length; i++ {
+		diff := a.Index(i) - mean
+		sum2 += diff * diff
+		sum3 += diff * diff * diff
+	}
+	if length <= 2 || sum2 == 0 {
+		return math.NaN()
+	}
+	l := float64(length)
+	return l * math.Sqrt(l-1) / (l - 2) * sum3 / math.Pow(sum2, 1.5)
+}
+
 // TODO: ta.linreg

pkg/types/indicator_test.go

@@ -56,3 +56,31 @@ func TestCorr(t *testing.T) {
 	corr = Correlation(&a, &b, 4, Spearman)
 	assert.InDelta(t, corr, -0.94868, 0.001)
 }
+
+/*
+python
+
+import pandas as pd
+s1 = pd.Series([.2, 0., .6, .2, .2])
+s2 = pd.Series([.3, .6, .0, .1])
+print(s1.cov(s2, ddof=0))
+*/
+func TestCov(t *testing.T) {
+	var a = Float64Slice{.2, .0, .6, .2}
+	var b = Float64Slice{.3, .6, .0, .1}
+	cov := Covariance(&a, &b, 4)
+	assert.InDelta(t, cov, -0.042499, 0.001)
+}
+
+/*
+python
+
+import pandas as pd
+s1 = pd.Series([.2, 0., .6, .2, .2])
+print(s1.skew())
+*/
+func TestSkew(t *testing.T) {
+	var a = Float64Slice{.2, .0, .6, .2}
+	sk := Skew(&a, 4)
+	assert.InDelta(t, sk, 1.129338, 0.001)
+}