intensity_at_points | R Documentation |
Kernel Estimate Intensity at Data Points
intensity_at_points( x, bw, kernel = "gaussian", border = "local", normalise = FALSE, loo = FALSE )
x |
point pattern |
bw |
bandwidth. Gaussian sd=bw, Epanechnicov domain [-bw, bw]. |
kernel |
Either 'gaussian' or 'epanenchnikov' (partial matching) |
border |
Border correction to apply. One of 'none', 'local', 'global', 'toroidal'. |
normalise |
renormalise so that inverse sum = volume |
loo |
leave-one-out -estimate? Don't include point i for estimation of int(i) |
For border correction, the bounding box of the coordinates of x will be used, so at the moment it works only for axis-aligned cuboids.
The kernel will be a product of one dimensional kernels, so Epanechnikov in many dimensions will not be truly isotropic but prefers diagonal directions.
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