OPEN-SOURCE SCRIPT
Function - Kernel Density Estimation (KDE)
Updated
"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
In true TradingView spirit, the author of this script has published it open-source, so traders can understand and verify it. Cheers to the author! You may use it for free, but reuse of this code in publication is governed by House rules. You can favorite it to use it on a chart.
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