Kernel density estimation

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Notion

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Science and technology

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What Wikipedia says

In statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on kernels as weights.

Excerpt from the Wikipedia article “Kernel density estimation”, under the CC BY-SA 4.0 license. Read the article on Wikipedia

Image: M. W. Toews, CC BY-SA 4.0, via Wikimedia Commons.