/// <summary>A Vector extension method that variances the given x coordinate.</summary>
/// <param name="x">The x to act on.</param>
/// <returns>A double.</returns>
public static double Variance(this Vector x)
{
var mean = x.Mean();
var sum = 0d;
for (int i = 0; i < x.Length; i++)
{
sum += System.Math.Pow(x[i] - mean, 2);
}
return(sum / (x.Length - 1));
}
/// <summary>
/// A Vector extension method that computes variances the given x coordinate
/// </summary>
/// <param name="x">The source to act on.</param>
/// <param name="isSamplePop">is sample population?</param>
/// <returns>A double.</returns>
public static double Variance(this Vector x, bool isSamplePop = false)
{
var mean = x.Mean();
var sum = 0d;
for (int i = 0; i < x.Length; i++)
{
sum += System.Math.Pow(x[i] - mean, 2);
}
return(sum / (isSamplePop ? x.Length - 1 : x.Length));
}
/// <summary>A Vector extension method that covariances.</summary>
/// <exception cref="InvalidOperationException">Thrown when the requested operation is invalid.</exception>
/// <param name="x">The x to act on.</param>
/// <param name="y">The Vector to process.</param>
/// <returns>A double.</returns>
public static double Covariance(this Vector x, Vector y)
{
if (x.Length != y.Length)
{
throw new InvalidOperationException("Vectors must be the same length.");
}
var xmean = x.Mean();
var ymean = y.Mean();
var sum = 0d;
for (int i = 0; i < x.Length; i++)
{
sum += (x[i] - xmean) * (y[i] - ymean);
}
return(sum / (x.Length - 1));
}
/// <summary>
/// Computes the Coefficient of Variation of the Root Mean Squared Error for the given inputs.
/// </summary>
/// <param name="y1">Predicted values.</param>
/// <param name="y2">Actual values.</param>
/// <returns>Double.</returns>
public static double ComputeCoefRMSE(Vector y1, Vector y2)
{
return numl.Supervised.Score.ComputeRMSE(y1, y2) / y1.Mean();
}
