/// <summary>
/// Compute probability according to multivariate Gaussian
/// </summary>
/// <param name="x">Vector in question</param>
/// <param name="mu">Mean</param>
/// <param name="sigma">diag(covariance)</param>
/// <returns>Probability</returns>
private double Normal(Vector x, Vector mu, Vector sigma)
{
// 1 / (2pi)^(2/D) where D = length of sigma
var one_over_2pi = 1 / System.Math.Pow(2 * System.Math.PI, 2 / sigma.Length);
// 1 / sqrt(det(sigma)) where det(sigma) is the product of the diagonals
var one_over_det_sigma = System.Math.Sqrt(sigma.Aggregate(1d, (a, i) => a *= i));
// -.5 (x-mu).T sigma^-1 (x-mu) I have taken some liberties ;)
var exp = -0.5d * ((x - mu) * sigma.Each(d => 1 / d, true)).Dot(x - mu);
// e^(exp)
var e_exp = System.Math.Pow(System.Math.E, exp);
var result = one_over_2pi * one_over_det_sigma * e_exp;
return result;
}
