tEDM (version 1.0)

ic: intersection cardinality

Description

intersection cardinality

Usage

# S4 method for data.frame
ic(
  data,
  column,
  target,
  lib = NULL,
  pred = NULL,
  E = 2:10,
  tau = 0,
  k = E + 2,
  threads = length(pred),
  parallel.level = "low"
)

Value

A list

xmap

cross mapping 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 time lags.

k

(optional) number of nearest neighbors used in prediction.

threads

(optional) number of threads to use.

parallel.level

(optional) level of parallelism, low or high.

References

Tao, P., Wang, Q., Shi, J., Hao, X., Liu, X., Min, B., Zhang, Y., Li, C., Cui, H., Chen, L., 2023. Detecting dynamical causality by intersection cardinal concavity. Fundamental Research.

Examples

sim = logistic_map(x = 0.4,y = 0.4,step = 45,beta_xy = 0.5,beta_yx = 0)
ic(sim,"x","y",E = 4,k = 15:30,threads = 1)