KDE-Gaussian

"In statistics, kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable."
from wikipedia.com

發行說明

fixed a issue when using float type observations.
added a draw function to draw the KDE graph(you need to see all the bar history to see it, doesnt work for float observations)

發行說明

removed some redundant parameters, added bandwidth, nstep parameters, the graph looks stepd due to x axis havin interdigit floating numbers so it rounds to nearest causing that effect.

發行說明

improved the kde draw function