Function: gaussianKde()

function gaussianKde(samples): GaussianKde;

A Gaussian kernel density estimate with Scott's rule, identical to scipy's gaussian_kde(samples) in one dimension: the kernel variance is the samples' variance (with n − 1) times n^(−2/5), and the density at x is the mean of the kernels' densities.

Parameters

Parameter	Type
samples	ArrayLike<unknown>

Returns

GaussianKde

Throws

With fewer than two finite samples or zero variance (scipy's singular matrix).