simplex: simplex forecast

In spEDM: Spatial Empirical Dynamic Modeling

simplex forecast

Description

simplex forecast

Usage

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

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.

Value

A list

xmap

forecast performance

varname

name of target variable

method

method of cross mapping

tau

step of time lag

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"))

simplex(columbus,"inc","crime")

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