gccm: geographical convergent cross mapping

In spEDM: Spatial Empirical Dynamic Modeling

geographical convergent cross mapping

Description

geographical convergent cross mapping

Usage

## S4 method for signature 'sf'
gccm(
  data,
  cause,
  effect,
  libsizes = NULL,
  E = 3,
  tau = 1,
  k = E + 2,
  theta = 1,
  algorithm = "simplex",
  lib = NULL,
  pred = NULL,
  nb = NULL,
  threads = detectThreads(),
  parallel.level = "low",
  bidirectional = TRUE,
  detrend = TRUE,
  progressbar = TRUE
)

## S4 method for signature 'SpatRaster'
gccm(
  data,
  cause,
  effect,
  libsizes = NULL,
  E = 3,
  tau = 1,
  k = E + 2,
  theta = 1,
  algorithm = "simplex",
  lib = NULL,
  pred = NULL,
  threads = detectThreads(),
  parallel.level = "low",
  bidirectional = TRUE,
  detrend = TRUE,
  progressbar = TRUE
)

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.
theta	(optional) weighting parameter for distances, useful when algorithm is smap.
algorithm	(optional) prediction algorithm.
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.

Value

A list

xmap

cross mapping results

varname

names of causal and effect variable

bidirectional

whether to examine bidirectional causality

References

Gao, B., Yang, J., Chen, Z. et al. Causal inference from cross-sectional earth system data with geographical convergent cross mapping. Nat Commun 14, 5875 (2023).

Examples

columbus = sf::read_sf(system.file("case/columbus.gpkg", package="spEDM"))

g = gccm(columbus,"hoval","crime",libsizes = seq(5,45,5),E = 6)
g
plot(g, ylimits = c(0,0.85))

spEDM documentation built on June 25, 2025, 9:07 a.m.