Changeset 12134 for trunk/sources/HeuristicLab.Analysis/3.3/Statistics
- Timestamp:
- 03/05/15 10:22:03 (10 years ago)
- File:
-
- 1 edited
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trunk/sources/HeuristicLab.Analysis/3.3/Statistics/NormalDistribution.cs
r12012 r12134 28 28 public static class NormalDistribution { 29 29 public static double[] Density(double[] x, double mean, double stdDev) { 30 double[] result = new double[x.Length]; 30 return x.Select(xi => Density(xi, mean, stdDev)).ToArray(); 31 } 31 32 32 for (int i = 0; i < x.Length; i++) { 33 result[i] = (1.0 / (stdDev * Math.Sqrt(2.0 * Math.PI))) * 34 Math.Exp(-((Math.Pow(x[i] - mean, 2.0)) / 35 (2.0 * Math.Pow(stdDev, 2.0)))); 36 } 37 38 return result; 33 public static double Density(double x, double mean, double stdDev) { 34 return (1.0 / (stdDev * Math.Sqrt(2.0 * Math.PI))) * 35 Math.Exp(-((Math.Pow(x - mean, 2.0)) / 36 (2.0 * Math.Pow(stdDev, 2.0)))); 39 37 } 40 38 41 39 // based on the idea from http://www.statmethods.net/graphs/density.html 42 40 public static List<Tuple<double, double>> Density(double[] x, int nrOfPoints, double stepWidth) { 41 // calculate grid for which to estimate the density 43 42 double[] newX = new double[nrOfPoints]; 44 double mean = x.Average();45 double stdDev = x.StandardDeviation();46 43 double margin = stepWidth * 2; 47 44 … … 56 53 } 57 54 58 var y = Density(newX, mean, stdDev).Select(k => k * stepWidth * x.Length).ToList(); 55 // the scale (std.-dev. of the kernel is a parameter) 56 var sigma = 1.0; // TODO allow configuration in the view 57 // for each of the points for which we want to calculate the density 58 // we sum up all the densities of the observed points assuming they are at the center of a normal distribution 59 var y = from xi in newX 60 select (from obsX in x 61 select Density(xi, obsX, sigma)).Sum(); 59 62 60 var points = new List<Tuple<double, double>>(); 61 for (int i = 0; i < newX.Length; i++) { 62 points.Add(new Tuple<double, double>(newX[i], y[i])); 63 } 64 65 return points; 63 return newX.Zip(y, Tuple.Create).ToList(); 66 64 } 67 65 }
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