spEDM (version 1.7)

gcmc: geographical cross mapping cardinality

Description

geographical cross mapping cardinality

Usage

# S4 method for sf
gcmc(
  data,
  cause,
  effect,
  libsizes = NULL,
  E = 3,
  tau = 1,
  k = pmin(E^2),
  lib = NULL,
  pred = NULL,
  nb = NULL,
  threads = detectThreads(),
  parallel.level = "low",
  bidirectional = TRUE,
  detrend = FALSE,
  progressbar = TRUE
)
# S4 method for SpatRaster
gcmc(
  data,
  cause,
  effect,
  libsizes = NULL,
  E = 3,
  tau = 1,
  k = pmin(E^2),
  lib = NULL,
  pred = NULL,
  threads = detectThreads(),
  parallel.level = "low",
  bidirectional = TRUE,
  detrend = FALSE,
  progressbar = TRUE
)

Value

A list

xmap

cross mapping results

cs

causal strength

varname

names of causal and effect variable

bidirectional

whether to examine bidirectional causality

Arguments

data

observation data.

cause

name of causal variable.

effect

name of effect variable.

libsizes

(optional) number of spatial units used.

E

(optional) embedding dimensions.

tau

(optional) step of spatial lags.

k

(optional) number of nearest neighbors.

lib

(optional) libraries indices.

pred

(optional) predictions indices.

nb

(optional) neighbours list.

threads

(optional) number of threads to use.

parallel.level

(optional) level of parallelism, low or high.

bidirectional

(optional) whether to examine bidirectional causality.

detrend

(optional) whether to remove the linear trend.

progressbar

(optional) whether to show the progress bar.

Examples

columbus = sf::read_sf(system.file("case/columbus.gpkg", package="spEDM"))
# \donttest{
g = gcmc(columbus,"hoval","crime",E = 2,k = 25)
g
# }