fit_point_process: fit_point_process

Description Usage Arguments Details Value References Examples

View source: R/fit_point_process.R

Description

Create random patterns by point process fitting

Usage

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fit_point_process(
  pattern,
  n_random = 1,
  process = "poisson",
  return_input = TRUE,
  simplify = FALSE,
  verbose = TRUE
)

Arguments

pattern

List with reconstructed patterns.

n_random

Number of randomized RasterLayers.

process

What point process to use. Either 'poisson' or 'cluster'.

return_input

The original input data is returned as last list entry.

simplify

If n_random = 1 and return_input = FALSE only pattern will be returned.

verbose

Print progress report.

Details

The functions randomizes the observed pattern by fitting a point process to the data. It is possible to choose between a Poisson process or a Thomas cluster process.

Value

list

References

Plotkin, J. B., Potts, M. D., Leslie, N., Manokaran, N., LaFrankie, J. V., & Ashton, P. S. (2000). Species-area curves, spatial aggregation, and habitat specialization in tropical forests. Journal of Theoretical Biology, 207(1), 81-99.

Examples

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pattern_fitted <- fit_point_process(pattern = species_a, n_random = 39)

mhesselbarth/SHAR documentation built on Oct. 17, 2020, 8:58 p.m.