summ_func_random_labelling: Summary functions for random labelling

In myllym/marksummary: Calculate summary functions for marked point patterns

Description

Calculates summary functions for a pattern and its simulations under the hypothesis of random labelling.

Usage

summ_func_random_labelling(pattern, edge_correction = "translate",
  mtf_name = c("1", "m", "mm", "gamma", "gammaAbs", "morAbs"), nsim = 999L,
  r_max = NULL, r_vec = NULL, do_besags_L = TRUE, method = "permute",
  use_biased_lambda2 = FALSE, ...)

Arguments

pattern	A ppp object as the simple marked point pattern to be analysed. The marks need to be in the form of a numeric vector. The window has to have the type "rectangle".
edge_correction	The name of the edge correction to be used. Options are 'translate' and 'none'.
mtf_name	A vector of mark test function names. "1" stands for the unmarked K-function. Accepted values are '1', 'm', 'mm', 'gamma', 'gammaAbs' and 'morAbs'.
nsim	The number of permutations.
r_max	A positive scalar value representing the maximum radius that should be considered. r_vec overrides r_max. By default, r_max is NULL and will get a sensible default.
r_vec	A monotonically increasing vector of non-negative r-values to act as the endpoints of the bins for the K_f-functions. r_vec overrides r_max. The bins are exclusive on the left and inclusive on the right. If the first vector element has value zero, it will be regarded as the collapsed bin [0, 0], and the next bin will start from and exclude 0.
do_besags_L	A boolean describing whether Besag's L-function should also be returned where available.
method	The name of the method to create simulations under the null hypothesis. 'permute' results in permutations of the marks. Using 'sample' will sample the marks from the empirical mark distribution with replacement. 'permute' is the default.
use_biased_lambda2	A logical scalar on whether to use the biased or the unbiased (in the Poisson case) estimate of the intensity squared.
...	Currently unused.

Value

A list containing the radius vector (r) and an array (a) containing the summary function estimates for the original pattern and the randomly labelled patterns with dimensions orig_and_perm, summ_func, r. The estimates for the given marked point pattern are on the row named "original".

Examples

require(spatstat)
pp <- spruces
res <- summ_func_random_labelling(pp)

myllym/marksummary documentation built on May 23, 2019, 11:59 a.m.