Kest_gaussian: Gaussian Weighted Sum of Pairwise Vectors

In antiphon/Kdirectional: Analysis of anisotropy in point patterns using second order statistics

Gaussian Weighted Sum of Pairwise Vectors

Description

Estimate K function -type summary for second order reweighted ("inhomogeneous") pattern using a Gaussian kernel sitting in the origin of the Fry-plot.

Usage

Kest_gaussian(
  x,
  u,
  kappa,
  r,
  lambda = NULL,
  lambda_h,
  renormalise = TRUE,
  border = 1,
  ...
)

Arguments

x	pp, list with $x~coordinates $bbox~bounding box
u	unit vector(s) of direction, as row vectors. Default: x and y axes, viz. c(1,0) and c(0,1). This gives the major axis of the ellipsoid (direction of largest variance in the Gaussian density).
kappa	The ratio of the secondary axis to the main axis going along 'u'.
r	radius vector at which to evaluate. Corresponds to the radii of the 95% quantile in x-axis, before rotation in directions u.
lambda	optional vector of intensity estimates at points
lambda_h	if lambda missing, use this bandwidth in a kernel estimate of lambda(x)
renormalise	See details.
border	Use border correction? Default=1, yes. At the moment no other version available!
...	passed on to e.g. intensity_at_points

Details

TODO Gaussian kernel sitting at the fry-space, sum over fry-points.

Value

Returns a dataframe.

antiphon/Kdirectional documentation built on Feb. 13, 2023, 6:26 a.m.