krst plot

Kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable. It is commonly used in data analysis and visualization to smooth out data and see underlying patterns more clearly.

Below are some software products that can be used for generating kernel density plots:

  • R
    より

    R

    A popular open-source statistical computing software that includes functions for KDE and data visualization. もっと読む
  • Python
    より

    Python

    A versatile programming language with libraries like seaborn and scipy that offer tools for KDE plotting. もっと読む
  • MATLAB
    より

    MATLAB

    A high-level programming language and interactive environment for numerical computation, visualization, and machine learning. もっと読む

If you are looking for alternatives, here are some other software products for generating kernel density plots:

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krst plot