false nearest neighbours

Usage

# S4 method for class 'sf'
fnn(
  data,
  target,
  E = 1:10,
  tau = 1,
  style = 1,
  lib = NULL,
  pred = NULL,
  dist.metric = "L1",
  rt = 10,
  eps = 2,
  threads = detectThreads(),
  detrend = TRUE,
  nb = NULL
)

# S4 method for class 'SpatRaster'
fnn(
  data,
  target,
  E = 1:10,
  tau = 1,
  style = 1,
  lib = NULL,
  pred = NULL,
  dist.metric = "L1",
  rt = 10,
  eps = 2,
  threads = detectThreads(),
  detrend = TRUE,
  grid.coord = TRUE
)

Arguments

data: observation data.
target: name of target variable.
E: (optional) embedding dimensions.
tau: (optional) step of spatial lags.
style: (optional) embedding style (0 includes current state, 1 excludes it).
lib: (optional) libraries indices.
pred: (optional) predictions indices.
dist.metric: (optional) distance metric (L1: Manhattan, L2: Euclidean).
rt: (optional) escape factor.
eps: (optional) neighborhood diameter.
threads: (optional) number of threads to use.
detrend: (optional) whether to remove the linear trend.
nb: (optional) neighbours list.
grid.coord: (optional) whether to detrend using cell center coordinates (TRUE) or row/column numbers (FALSE).

Value

A vector

References

Kennel M. B., Brown R. and Abarbanel H. D. I., Determining embedding dimension for phase-space reconstruction using a geometrical construction, Phys. Rev. A, Volume 45, 3403 (1992).

Examples

columbus = sf::read_sf(system.file("case/columbus.gpkg", package="spEDM"))
# \donttest{
fnn(columbus,"crime")
#>        E:1        E:2        E:3        E:4        E:5        E:6        E:7 
#> 0.79591837 0.53061224 0.63265306 0.51020408 0.12244898 0.04081633 0.00000000 
#>        E:8 
#> 0.00000000 
# }