Kernel density (2D)

Makes a smooth map of point density in 2D. Two columns of x/y coordinates in a rectangular domain are expected. The user can specify the size of the grid (number of rows and columns). The “Radius” value sets the scale r of the kernel. There is currently no automatic selection of “optimal” radius, so this value must be set by the user depending on the scale of interest.

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The density estimate is based on one of four kernel functions, with radius parameter r: Gaussian, parabolic, triangular, uniform. For equations, see the Past manual.

The scaling gives an estimate of the number of points per area, not a probability density. The gaussian and paraboloid (quadratic) kernels usually perform best. The uniform kernel gives very low smoothness.

Published Aug. 31, 2020 8:21 PM - Last modified Apr. 6, 2022 3:07 PM