OPEN-SOURCE SCRIPT
已更新

Function - Kernel Density Estimation (KDE)

10 624
"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:
  • Uniform
  • Triangle
  • Epanechnikov
  • Quartic
  • Triweight
  • Gaussian
  • Cosinus


Republishing due to change of function.
deprecated script:
KDE-Gaussian
版本注释
added quartic and triweight kernels.
版本注释
  • added placeholder for kernels(logistic, sigmoid, silverman)
  • added kernel calculations for kernel(uniform, triangular, cosine)
版本注释
added calculations for kernels(logistic, sigmoid and silverman(Not working atm)
版本注释
removed silverman kernel, added highest value index line/label, nearest to 0 index as a dotted gray line.
版本注释
added extra stats/visuals to drawing function.

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