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

發布通知:

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)

發布通知:

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.

發布通知:

improved the kde draw function