simplex: simplex forecast

In tEDM: Temporal Empirical Dynamic Modeling

simplex forecast

Description

simplex forecast

Usage

## S4 method for signature 'data.frame'
simplex(
  data,
  column,
  target,
  lib = NULL,
  pred = NULL,
  E = 2:10,
  tau = 1,
  k = E + 1,
  dist.metric = "L1",
  dist.average = TRUE,
  threads = length(E)
)

## S4 method for signature 'list'
simplex(
  data,
  column,
  target,
  lib = NULL,
  pred = NULL,
  E = 2:10,
  tau = 1,
  k = E + 1,
  dist.metric = "L1",
  dist.average = TRUE,
  threads = length(E)
)

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 time lags.
k	(optional) number of nearest neighbors used in prediction.
dist.metric	(optional) distance metric (L1: Manhattan, L2: Euclidean).
dist.average	(optional) whether to average distance.
threads	(optional) number of threads to use.

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

sim = logistic_map(x = 0.4,y = 0.4,step = 45,beta_xy = 0.5,beta_yx = 0)
simplex(sim,"x","y",E = 4:10,k = 7,threads = 1)

tEDM documentation built on Aug. 25, 2025, 5:12 p.m.