SPUG: RFC: Statistics::KernelEstimation - Kernel Density Estimates and Histograms
Philipp K. Janert
janert at ieee.org
Sun Nov 23 16:22:08 PST 2008
I would like to invite comments on a new module, named
This modules calculates Kernel Density Estimates and related
quantities for a collection of random points.
A Kernel Density Estimate (KDE) is similar to a histogram,
but improves on two known problems of histograms: it is
smooth (whereas a histogram is ragged) and does not suffer
from ambiguity in regards to the placement of bins.
In a KDE, a smooth, strongly peaked function is placed at the
location of each point in the collection, and the contributions
from all points is summed. The resulting function is a smooth
approximation to the probability density from which the set of
points was drawn.
This module calculates KDEs as well as Cumulative Density
Functions (CDF). Three different kernels are available
(Gaussian, Box, Epanechnikov).
The module also includes limited support for bandwidth optimization.
Finally, the module can generate "classical" histograms and
The full POD is available here:
Let me know what you think!
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