spEDM (version 1.7)

simplex: simplex forecast

Description

simplex forecast

Usage

# S4 method for sf
simplex(
  data,
  column,
  target,
  lib = NULL,
  pred = NULL,
  E = 1:10,
  tau = 1,
  k = E + 2,
  nb = NULL,
  threads = detectThreads(),
  detrend = TRUE
)
# S4 method for SpatRaster
simplex(
  data,
  column,
  target,
  lib = NULL,
  pred = NULL,
  E = 1:10,
  tau = 1,
  k = E + 2,
  threads = detectThreads(),
  detrend = TRUE
)

Value

A list

xmap

forecast performance

varname

name of target variable

method

method of cross mapping

tau

step of time lag

Arguments

data

observation data.

column

name of library variable.

target

name of target variable.

lib

(optional) libraries indices.

pred

(optional) predictions indices.

E

(optional) embedding dimensions.

tau

(optional) step of spatial lags.

k

(optional) number of nearest neighbors used.

nb

(optional) neighbours list.

threads

(optional) number of threads to use.

detrend

(optional) whether to remove the linear trend.

References

Sugihara G. and May R. 1990. Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series. Nature, 344:734-741.

Examples

columbus = sf::read_sf(system.file("case/columbus.gpkg", package="spEDM"))
# \donttest{
simplex(columbus,"inc","crime")
# }