Applications of Empirical Dynamic Modeling from Time Series


[Up] [Top]

Documentation for package ‘rEDM’ version 0.4.7

Help Pages

rEDM-package Applications of empirical dynamic modeling from time series.
BlockLNLP C++ compiled object for multivariate forecasting.
block_3sp Time series for a three-species coupled model.
block_lnlp Perform generalized forecasting using simplex projection or s-map
ccm Perform convergent cross mapping using simplex projection
ccm_means Take output from ccm and compute means as a function of library size.
e054_succession Succession data at the Cedar Creek LTER
e120_biodiversity Biodiversity data at the Cedar Creek LTER
LNLP C++ compiled object for univariate forecasting.
make_surrogate_data Generate surrogate data for permutation/randomization tests
paramecium_didinium Time series for the Paramecium-Didinium laboratory experiment
Rcpp_BlockLNLP-class S4 class for Rcpp compiled object, "BlockLNLP"
Rcpp_LNLP-class S4 class for Rcpp compiled object, "LNLP"
Rcpp_Xmap-class S4 class for Rcpp compiled object, "Xmap"
rEDM Applications of empirical dynamic modeling from time series.
sardine_anchovy_sst Time series for the California Current Anchovy-Sardine-SST system
simplex Perform univariate forecasting
sockeye_returns Time series for sockeye salmon returns.
s_map Perform univariate forecasting
tentmap_del Time series for a tent map with mu = 2.
test_nonlinearity Randomization test for nonlinearity using S-maps and surrogate data
thrips_block Apple-blossom Thrips time series
two_species_model Time series for a two-species coupled model.
Xmap C++ compiled object for convergent cross mapping.