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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
Nota Keluaran
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)
Nota Keluaran
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.
Nota Keluaran
improved the kde draw function

Penafian