spEDM (version 1.7)

multiview: multiview embedding forecast

Description

multiview embedding forecast

Usage

# S4 method for sf
multiview(
  data,
  column,
  target,
  nvar,
  lib = NULL,
  pred = NULL,
  E = 3,
  tau = 1,
  k = E + 2,
  nb = NULL,
  top = NULL,
  threads = detectThreads(),
  detrend = TRUE
)
# S4 method for SpatRaster
multiview(
  data,
  column,
  target,
  nvar,
  lib = NULL,
  pred = NULL,
  E = 3,
  tau = 1,
  k = E + 2,
  top = NULL,
  threads = detectThreads(),
  detrend = TRUE
)

Value

A vector (when input is sf object) or matrix

Arguments

data

observation data.

column

name of library variable.

target

name of target variable.

nvar

number of variable combinations.

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.

top

(optional) number of reconstructions used in MVE forecast.

threads

(optional) number of threads to use.

detrend

(optional) whether to remove the linear trend.

References

Ye H., and G. Sugihara, 2016. Information leverage in interconnected ecosystems: Overcoming the curse of dimensionality. Science 353:922-925.

Examples

columbus = sf::read_sf(system.file("case/columbus.gpkg", package="spEDM"))
# \donttest{
multiview(columbus,
          column = c("inc","crime","open","plumb","discbd"),
          target = "hoval", nvar = 3)
# }