spEDM (version 1.9)

slm: spatial logistic map

Description

spatial logistic map

Usage

# S4 method for sf
slm(
  data,
  x = NULL,
  y = NULL,
  z = NULL,
  k = 4,
  step = 15,
  alpha_x = 0.28,
  alpha_y = 0.25,
  alpha_z = 0.22,
  beta_xy = 0.05,
  beta_xz = 0.05,
  beta_yx = 0.2,
  beta_yz = 0.2,
  beta_zx = 0.35,
  beta_zy = 0.35,
  threshold = Inf,
  transient = 1,
  interact = "local",
  aggregate_fn = NULL,
  nb = NULL
)
# S4 method for SpatRaster
slm(
  data,
  x = NULL,
  y = NULL,
  z = NULL,
  k = 4,
  step = 15,
  alpha_x = 0.28,
  alpha_y = 0.25,
  alpha_z = 0.22,
  beta_xy = 0.05,
  beta_xz = 0.05,
  beta_yx = 0.2,
  beta_yz = 0.2,
  beta_zx = 0.35,
  beta_zy = 0.35,
  threshold = Inf,
  transient = 1,
  interact = "local",
  aggregate_fn = NULL
)

Value

A list

Arguments

data

observation data.

x

(optional) name of first spatial variable.

y

(optional) name of second spatial variable.

z

(optional) name of third spatial variable.

k

(optional) number of neighbors to used.

step

(optional) number of simulation time steps.

alpha_x

(optional) growth parameter for x.

alpha_y

(optional) growth parameter for y.

alpha_z

(optional) growth parameter for z.

beta_xy

(optional) cross-inhibition from x to y.

beta_xz

(optional) cross-inhibition from x to z.

beta_yx

(optional) cross-inhibition from y to x.

beta_yz

(optional) cross-inhibition from y to z.

beta_zx

(optional) cross-inhibition from z to x.

beta_zy

(optional) cross-inhibition from z to y.

threshold

(optional) set to NaN if the absolute value exceeds this threshold.

transient

(optional) transients to be excluded from the results.

interact

(optional) type of cross-variable interaction (local or neighbors).

aggregate_fn

(optional) Custom aggregation function. Must accept a numeric vector and return a single numeric value.

nb

(optional) neighbours list.

References

Willeboordse, F.H., The spatial logistic map as a simple prototype for spatiotemporal chaos, Chaos, 533–540 (2003).

Examples

columbus = sf::read_sf(system.file("case/columbus.gpkg",package="spEDM"))
columbus$inc = sdsfun::normalize_vector(columbus$inc)
slm(columbus,"inc")