Analysis

Esiur.Analysis/Statistics/Probability.cs

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+using Esiur.Analysis.Units;
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace Esiur.Analysis.Statistics
+{
+    public struct Probability
+    {
+        public double Value;
+
+        public static implicit operator Probability(double v) => new Probability(v);
+        public static implicit operator double(Probability v) => v.Value;
+
+        public Probability(double value)
+        {
+            if (value > 1 || value < 0)
+                throw new Exception("0 >= Probability <= 1");
+
+            Value = value;
+        }
+
+        public double ToPercentage() => Value * 100;
+        public Probability FromPercentage(double value) => new Probability(value / 100);
+
+        public override string ToString()
+        {
+            return (Math.Round(Value * 10000) / 100) + "%";
+        }
+    }
+}

Esiur.Analysis/Statistics/StatisticalFunctions.cs

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+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+
+namespace Esiur.Analysis.Statistics
+{
+    public static class Statistics
+    {
+        public static double Mean(this double[] values) => values.Sum() / values.Length;
+
+        public static double Variance(this double[] x)
+        {
+            var mean = x.Mean();
+            return x.Sum(x => Math.Pow(x - mean, 2)) / x.Length;
+        }
+
+
+        public static double StdDiv(this double[] x) => Math.Sqrt(x.Variance());
+
+        public static double Covariance(this double[] x, double[] y)
+        {
+            var n = x.Length < y.Length ? x.Length : y.Length;
+            var X = x.Mean();
+            var Y = y.Mean();
+
+            double rt = 0;
+
+            for (var i = 0; i < n; i++)
+                rt += (x[i] - X) * (y[i] - Y);
+
+            return rt / n;
+        }
+
+
+        public static double RMS(this double[] x) => Math.Sqrt(x.Sum(x => x * x) / x.Length);
+
+
+        public static double Correlation(this double[] x, double[] y)
+        {
+            return x.Covariance(y) / (x.StdDiv() * y.StdDiv());
+        }
+    }
+}