Inhomogeneous anisotropic mark-correlation function, sector version
Source:R/markcorr_anin.R
markcorr_anin.RdEstimate a sector-mark correlation function for second order reweighted "inhomogeneous" pattern.
Usage
markcorr_anin(
x,
marks,
u,
epsilon,
r,
lambda = NULL,
lambda_h,
f = function(a, b) a * b,
r_h,
stoyan = 0.15,
renormalise = TRUE,
bootsize = 1e+05,
normaliser = NULL,
border = 1,
divisor = "d",
...
)Arguments
- x
pp, list with $x~coordinates $bbox~bounding box
- marks
if x is not marked (x$marks is empty), use these marks
- 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
- lambda
optional vector of intensity estimates at points
- lambda_h
if lambda missing, use this bandwidth in a kernel estimate of lambda(x)
- f
test function of the form function(m1, m2) ..., returning a vector of length(m1). default: m1*m2
- 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.
- bootsize
bootstrap size for estimating the normaliser if not given.
- normaliser
normalising constant under independent marking. If NULL, estimated with bootstrap.
- border
Use translation correction? Default=1, yes. Only for cuboidal windows.
- divisor
either "d" or "r". Divide by dist(i,j) ("d") instead of r ("r")?
- ...
passed on to e.g. intensity_at_points
Details
Computes a second order reweighted version of the mark correlation function.
lambda(x) at points can be given, or else it will be estimated using Epanechnikov kernel smoothing. See
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'.