Kernel Density Estimates From Points | R Documentation |
Given a set of points, a bandwidth, a grid density and a frame, produce a kernel density estimate
kde.points(pts,h,n=200,lims=NULL)
pts |
A |
h |
A real number - the bandwidth of the KDE |
n |
An integer, the output grid density - ie result is nxn grid |
lims |
A spatial object - the KDE grid will cover this, if provided |
A SpatialPixelsDataFrame
containing the KDE.
Chris Brunsdon, Binbin Lu
# Data for New Haven to use in example
data(newhaven)
# Do the KDE
breach.dens = kde.points(breach,lims=tracts)
# Plot the result
level.plot(breach.dens)
# Block out the part outside the study area
masker = poly.outer(breach.dens,tracts,extend=100); add.masking(masker)
# Plot census tract boundaries
plot(tracts,add=TRUE)
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