Pattern reconstruction for clustered patterns
Usage
reconstruct_pattern_cluster(
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,
r_max = NULL,
return_input = TRUE,
simplify = FALSE,
verbose = TRUE,
plot = FALSE
)
Arguments
- 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
e_threshold
is not reached.- 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
r = 0
tor = rmax
for which the summary functions are evaluated.- r_max
Double with maximum distance used during calculation of summary functions. If
NULL
, will be estimated from data.- return_input
Logical if the original input data is returned.
- simplify
Logical if only pattern will be returned if
n_random = 1
andreturn_input = FALSE
.- verbose
Logical if progress report is printed.
- plot
Logical if pcf(r) function is plotted and updated during optimization.
References
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