Initial commit

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

common/maths/correlation.go

@@ -0,0 +1,44 @@
+package maths
+
+import "math"
+
+func Correlation(data1, data2 Float64Data) (float64, error) {
+	l1 := data1.Len()
+	l2 := data2.Len()
+	if l1 == 0 || l2 == 0 {
+		return math.NaN(), EmptyInputErr
+	}
+	if l1 != l2 {
+		return math.NaN(), SizeErr
+	}
+	sdev1, _ := StandardDeviationPopulation(data1)
+	sdev2, _ := StandardDeviationPopulation(data2)
+	if sdev1 == 0 || sdev2 == 0 {
+		return 0, nil
+	}
+	covp, _ := CovariancePopulation(data1, data2)
+	return covp / (sdev1 * sdev2), nil
+}
+
+func Pearson(data1, data2 Float64Data) (float64, error) {
+	return Correlation(data1, data2)
+}
+
+func AutoCorrelation(data Float64Data, lags int) (float64, error) {
+	if len(data) < 1 {
+		return 0, EmptyInputErr
+	}
+	mean, _ := Mean(data)
+	var result, q float64
+	for i := 0; i < lags; i++ {
+		v := (data[0] - mean) * (data[0] - mean)
+		for i := 1; i < len(data); i++ {
+			delta0 := data[i-1] - mean
+			delta1 := data[i] - mean
+			q += (delta0*delta1 - q) / float64(i+1)
+			v += (delta1*delta1 - v) / float64(i+1)
+		}
+		result = q / v
+	}
+	return result, nil
+}