smap forecast

Usage

# S4 method for class '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)
#> The suggested theta for variable y is 0