ic {tEDM} | R Documentation |
intersection cardinality
Description
intersection cardinality
Usage
## S4 method for signature 'data.frame'
ic(
data,
column,
target,
lib = NULL,
pred = NULL,
E = 2:10,
tau = 0,
k = E + 2,
threads = length(pred),
parallel.level = "low"
)
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, |
Value
A list
xmap
cross mapping performance
varname
name of target variable
method
method of cross mapping
tau
step of time lag
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)
[Package tEDM version 1.0 Index]