Runs pairwise CCM based on the simplex_output - using the best
embedding dimension from the simplex results, and computed for both the
real data and the surrogate data. The calculations run using
furrr::future_pmap(). Thus, parallelization should be set by the user,
if desired, using future::plan(), prior to running.
compute_ccm(simplex_results, lib_sizes = seq(10, 100, by = 10), random_libs = TRUE, num_samples = 100, replace = TRUE, RNGseed = 42, silent = TRUE)
| simplex_results | the output of |
|---|---|
| lib_sizes | the vector of library sizes to try |
| random_libs | indicates whether to use randomly sampled libs |
| num_samples | is the number of random samples at each lib size (this parameter is ignored if random_libs is FALSE) |
| replace | indicates whether to sample vectors with replacement |
| RNGseed | will set a seed for the random number generator, enabling reproducible runs of ccm with randomly generated libraries |
| silent | prevents warning messages from being printed to the R console |
A tibble with columns for the variables that we use in CCM, the data type (whether it's the "actual" time series or "surrogate"), the library size, and the results from CCM