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
In true TradingView spirit, the creator of this script has made it open-source, so that traders can review and verify its functionality. Kudos to the author! While you can use it for free, remember that republishing the code is subject to our House Rules.
Disclaimer
The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView. Read more in the Terms of Use.
Open-source script
In true TradingView spirit, the creator of this script has made it open-source, so that traders can review and verify its functionality. Kudos to the author! While you can use it for free, remember that republishing the code is subject to our House Rules.
Disclaimer
The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView. Read more in the Terms of Use.