ccm_means is a utility function to summarize output from the ccm function. If there is a model_output column (e.g. if ccm() was run with stats_only = FALSE), then that column is dropped before summaries are computed.

ccm_means(ccm_df, FUN = mean, ...)

## Arguments

ccm_df a data.frame, usually output from the ccm function a function that aggregates the numerical statistics (by default, uses the mean) optional arguments to FUN

## Value

A data.frame with forecast statistics aggregated at each unique library size

## Examples

data("sardine_anchovy_sst")
anchovy_xmap_sst <- ccm(sardine_anchovy_sst, E = 3,
lib_column = "anchovy", target_column = "np_sst",
lib_sizes = seq(10, 80, by = 10), num_samples = 100)#> Warning: Note: CCM results are typically interpreted in the opposite direction of causation. Please see 'Detecting causality in complex ecosystems' (Sugihara et al. 2012) for more details.#> Warning: Found overlap between lib and pred. Enabling cross-validation with exclusion radius = 0.a_xmap_t_means <- ccm_means(anchovy_xmap_sst)