kernel2d {splancs} | R Documentation |
Perform kernel smoothing of a point pattern
kernel2d(pts,poly,h0,nx=20,ny=20,kernel='quartic')
pts |
A points data set |
poly |
A polygon data set |
h0 |
The kernel width parameter |
nx |
Number of points along the x-axis of the returned grid. |
ny |
Number of points along the y-axis of the returned grid. |
kernel |
Type of kernel function to use. Currently only the quartic kernel is implemented. |
The kernel estimate, with a correction for edge effects, is computed for
a grid of points that span the
input polygon. The kernel function for points in the grid that are outside the polygon are returned
as NA's.
The output list is in a format that can be read into image()
directly,
for display and superposition onto other plots.
A list with the following components:
x |
List of x-coordinates at which the kernel function has been evaluated. |
y |
List of y-coordinates at which the kernel function has been evaluated. |
z |
A matrix of dimension nx by ny containing the value of
the kernel function. |
h0, kernel |
containing the values input to kernel2d |
Berman M. and Diggle P.J. (1989) Estimating Weighted Integrals of the Second-Order Intensity of Spatial Point Patterns. J. R. Statist Soc B51 81-92; Rowlingson, B. and Diggle, P. 1993 Splancs: spatial point pattern analysis code in S-Plus. Computers and Geosciences, 19, 627-655, (Barry Rowlingson ); the original sources can be accessed at: http://www.maths.lancs.ac.uk/~rowlings/Splancs/. See also Bivand, R. and Gebhardt, A. 2000 Implementing functions for spatial statistical analysis using the R language. Journal of Geographical Systems, 2, 307-317.
data(bodmin) plot(bodmin$poly, asp=1, type="n") image(kernel2d(as.points(bodmin), bodmin$poly, h0=2, nx=100, ny=100), add=TRUE, col=terrain.colors(20)) pointmap(as.points(bodmin), add=TRUE) polymap(bodmin$poly, add=TRUE)