smap {tEDM} | R Documentation |
smap forecast
Description
smap forecast
Usage
## S4 method for signature 'data.frame'
smap(
data,
column,
target,
lib = NULL,
pred = NULL,
E = 3,
tau = 0,
k = E + 1,
theta = c(0, 1e-04, 3e-04, 0.001, 0.003, 0.01, 0.03, 0.1, 0.3, 0.5, 0.75, 1, 1.5, 2, 3,
4, 6, 8),
threads = length(theta)
)
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. |
theta |
(optional) weighting parameter for distances. |
threads |
(optional) number of threads to use. |
Value
A list
xmap
forecast performance
varname
name of target variable
method
method of cross mapping
References
Sugihara G. 1994. Nonlinear forecasting for the classification of natural time series. Philosophical Transactions: Physical Sciences and Engineering, 348 (1688):477-495.
Examples
sim = logistic_map(x = 0.4,y = 0.4,step = 45,beta_xy = 0.5,beta_yx = 0)
smap(sim,"x","y",E = 8,k = 7,threads = 1)
[Package tEDM version 1.0 Index]