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  2. Kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Kernel_density_estimation

    Kernel density estimation of 100 normally distributed random numbers using different smoothing bandwidths.. 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.

  3. Multivariate kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Multivariate_kernel...

    The previous figure is a graphical representation of kernel density estimate, which we now define in an exact manner. Let x 1, x 2, ..., x n be a sample of d-variate random vectors drawn from a common distribution described by the density function ƒ.

  4. Kernel regression - Wikipedia

    en.wikipedia.org/wiki/Kernel_regression

    Python: the KernelReg class for mixed data types in the statsmodels.nonparametric sub-package (includes other kernel density related classes), the package kernel_regression as an extension of scikit-learn (inefficient memory-wise, useful only for small datasets) R: the function npreg of the np package can perform kernel regression. [7] [8]

  5. LabPlot - Wikipedia

    en.wikipedia.org/wiki/LabPlot

    LabPlot is a free and open-source, cross-platform computer program for interactive scientific plotting, curve fitting, nonlinear regression, data processing and data analysis. LabPlot is available, under the GPL-2.0-or-later license, for Windows, macOS, Linux, FreeBSD and Haiku operating systems.

  6. Matplotlib - Wikipedia

    en.wikipedia.org/wiki/Matplotlib

    Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.

  7. Kig (software) - Wikipedia

    en.wikipedia.org/wiki/Kig_(software)

    Kig comes up with a little program (written in Python) called pykig.py which can load a Python script, e.g. MyScript.py; build a Kig figure, described by this script; open Kig and display the figure. For example, here is how a Sierpinski triangle can be made (as an IFS) with pykig:

  8. Generalized additive model for location, scale and shape

    en.wikipedia.org/wiki/Generalized_additive_model...

    The first two population distribution parameters and are usually characterized as location and scale parameters, while the remaining parameter(s), if any, are characterized as shape parameters, e.g. skewness and kurtosis parameters, although the model may be applied more generally to the parameters of any population distribution with up to four ...

  9. kst (software) - Wikipedia

    en.wikipedia.org/wiki/Kst_(software)

    kst-plot.kde.org Kst is a plotting and data viewing program. It is a general purpose plotting software program that evolved out of a need to visualize and analyze astronomical data, but has also found subsequent use in the real time display of graphical information.