Finds the integrated density of the best hyperplanes orthogonal to a given projection vector (assumes the data have zero mean vector). Used as projection index for projection pursuit to find minimum density hyperplanes.
f_md(v, X, P)a numeric vector of length ncol(X)
a numeric matrix (num_data x num_dimensions) to be projected on v
a list of parameters including (at least) $h (positive numeric bandwidth value), $alpha (positive numeric constraint width), $C (positive numeric affecting the slope of the penalty)
the value of the integrated density of the best hyperplane orthogonal to v