OPEN-SOURCE SCRIPT
已更新 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:
發行說明
added quartic and triweight kernels.發行說明
- added placeholder for kernels(logistic, sigmoid, silverman)
- added kernel calculations for kernel(uniform, triangular, cosine)
發行說明
added calculations for kernels(logistic, sigmoid and silverman(Not working atm)發行說明
removed silverman kernel, added highest value index line/label, nearest to 0 index as a dotted gray line.發行說明
added extra stats/visuals to drawing function.開源腳本
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.
免責聲明
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.
開源腳本
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.
免責聲明
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.