OPEN-SOURCE SCRIPT
Updated Function - Kernel Density Estimation (KDE)
"In statistics, kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable."
from wikipedia.com
KDE function with optional kernel:
Republishing due to change of function.
deprecated script:
from wikipedia.com
KDE function with optional kernel:
- Uniform
- Triangle
- Epanechnikov
- Quartic
- Triweight
- Gaussian
- Cosinus
Republishing due to change of function.
deprecated script:
Release Notes
added quartic and triweight kernels.Release Notes
- added placeholder for kernels(logistic, sigmoid, silverman)
- added kernel calculations for kernel(uniform, triangular, cosine)
Release Notes
added calculations for kernels(logistic, sigmoid and silverman(Not working atm)Release Notes
removed silverman kernel, added highest value index line/label, nearest to 0 index as a dotted gray line.Release Notes
added extra stats/visuals to drawing function.
Open-source script
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