View source: R/reconstruct_pattern_hetero.R
reconstruct_pattern_hetero | R Documentation |
Pattern reconstruction for heterogeneous patterns
reconstruct_pattern_hetero( pattern, n_random = 1, e_threshold = 0.01, max_runs = 1000, no_change = Inf, annealing = 0.01, comp_fast = 1000, weights = c(0.5, 0.5), r_length = 250, return_input = TRUE, simplify = FALSE, verbose = TRUE, plot = FALSE )
pattern |
ppp object with pattern. |
n_random |
Integer with number of randomizations. |
e_threshold |
Double with minimum energy to stop reconstruction. |
max_runs |
Integer with maximum number of iterations if |
no_change |
Integer with number of iterations at which the reconstruction will stop if the energy does not decrease. |
annealing |
Double with probability to keep relocated point even if energy did not decrease. |
comp_fast |
Integer with threshold at which summary functions are estimated in a computational fast way. |
weights |
Vector with weights used to calculate energy. The first number refers to Gest(r), the second number to pcf(r). |
r_length |
Integer with number of intervals from |
return_input |
Logical if the original input data is returned. |
simplify |
Logical if only pattern will be returned if |
verbose |
Logical if progress report is printed. |
plot |
Logical if pcf(r) function is plotted and updated during optimization. |
rd_pat
Kirkpatrick, S., Gelatt, C.D.Jr., Vecchi, M.P., 1983. Optimization by simulated annealing. Science 220, 671–680. <https://doi.org/10.1126/science.220.4598.671>
Tscheschel, A., Stoyan, D., 2006. Statistical reconstruction of random point patterns. Computational Statistics and Data Analysis 51, 859–871. <https://doi.org/10.1016/j.csda.2005.09.007>
Wiegand, T., Moloney, K.A., 2014. Handbook of spatial point-pattern analysis in ecology. Chapman and Hall/CRC Press, Boca Raton. ISBN 978-1-4200-8254-8
## Not run: input_pattern <- spatstat.random::rpoispp(lambda = function(x, y) {100 * exp(-3 * x)}, nsim = 1) pattern_recon <- reconstruct_pattern_hetero(input_pattern, n_random = 19, max_runs = 1000) ## End(Not run)
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