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
from wikipedia.com
Notas de prensa:
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)
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)
Notas de prensa:
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.
Notas de prensa:
improved the kde draw function