The rEDM package is a new implementation of EDM algorithms based on research software previously developed for internal use in the Sugihara Lab (UCSD/SIO). Contains C++ compiled objects that use time delay embedding to perform state-space reconstruction and nonlinear forecasting and an R interface to those objects using Rcpp. It supports both the simplex projection method from Sugihara & May (1990) <DOI:10.1038/344734a0> and the S-map algorithm in Sugihara (1994) <DOI:10.1098/rsta.1994.0106>. In addition, this package implements convergent cross mapping as described in Sugihara et al. (2012) <DOI:10.1126/science.1227079> and multiview embedding as described in Ye & Sugihara (2016) <DOI:10.1126/science.aag0863>.
This package is divided into a set of main functions to perform various analyses, as well as helper functions that perform minor tasks, such as generate data, processing output, and wrapper functions.
Main Functions:
simplex
- simplex projection for univariate forecasting
s_map
- S-maps for univariate forecasting
block_lnlp
- simplex or S-map forecasting with a generic reconstructed state-space
ccm
- convergent cross mapping (causal inference)
multiview
- multi-model approach to forecasting
tde_gp
- Gaussian Processes for univariate forecasting
block_gp
- Gaussian Processes with a generic reconstructed state-space
Helper Functions:
compute_stats
- compute forecast skill metrics
ccm_means
- aggregate output of ccm
by library size ('lib_size')
make_surrogate_data
- generate surrogate time series
test_nonlinearity
- test for nonlinearity using surrogate time series
Maintainer: Hao Ye
Authors: Adam Clark, Ethan Deyle, Steve Munch
Contributors: Oliver Keyes, Jun Cai, Ethan White, Jane Cowles, James Stagge, Yair Daon, Andrew Edwards, George Sugihara
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.