Estimate a sector/cone pcf function for second order reweighted ("inhomogeneous") pattern.
Usage
pcf_anin(
x,
u,
epsilon,
r,
lambda = NULL,
lambda_h,
r_h,
stoyan = 0.15,
renormalise = TRUE,
border = 1,
divisor = "d",
...
)
Arguments
- x
pp, list with $x~coordinates $bbox~bounding box
- u
unit vector(s) of direction, as row vectors. Default: x and y axis.
- epsilon
Central half angle for the directed sector/cone (total angle of the rotation cone is 2*epsilon)
- r
radius vector at which to evaluate the function
- lambda
optional vector of intensity estimates at points
- lambda_h
if lambda missing, use this bandwidth in a kernel estimate of lambda(x)
- r_h
smoothing for range dimension, epanechnikov kernel
- stoyan
If r_h not given, use r_h=stoyan/lambda^(1/dim). Same as 'stoyan' in spatstat's pcf.
- renormalise
See details.
- border
Use translation correction? Default=1, yes. Only for cuboidal windows.
- divisor
See spatstat's pcf.ppp for this.
- ...
passed on to e.g. intensity_at_points
Details
Computes a second order reweighted version of the sector-pcf. The sector pcf differs from the true anisotropic pcf by assuming that the anisotropic pcf is constant over the small arc/cap of the sector, thus averaging over that data-area and providing more stable estimates.
Lambda(x) at points can be given, or else it will be estimated using kernel smoothing. See intensity_at_points.
If 'renormalise=TRUE', we normalise the lambda estimate so that sum(1/lambda(x))=|W|. This corresponds in spatstat
's Kinhom
to setting 'normpower=2'.