Title: Empirical Dynamic Modeling ('EDM')
Authors@R: c( person("Joseph", "Park", role = c("aut", "cre"),
person("Cameron", "Smith", role = c("aut"),
person("George", "Sugihara", role = c("aut", "ccp"),
person("Erik", "Saberski", role = c("ctb"),
Description: An implementation of 'EDM' algorithms based on research software developed for internal use at the Sugihara Lab ('UCSD/SIO').  The package is implemented with 'Rcpp' wrappers around the 'cppEDM' library.  It implements the 'simplex' projection method from Sugihara & May (1990) <doi:10.1038/344734a0>, the 'S-map' algorithm from Sugihara (1994) <doi:10.1098/rsta.1994.0106>, convergent cross mapping described in Sugihara et al. (2012) <doi:10.1126/science.1227079>, and, 'multiview embedding' described in Ye & Sugihara (2016) <doi:10.1126/science.aag0863>.
Author: Joseph Park [aut, cre] (<https://orcid.org/0000-0001-5411-1409>),
George Sugihara [aut, ccp] (<https://orcid.org/0000-0002-2863-6946>),

Description: An implementation of EDM algorithms based on research software developed for internal use at the Sugihara Lab (UCSD/SIO).  The package is implemented with 'Rcpp' wrappers around the 'cppEDM' library.  It implements the simplex projection method from Sugihara & May (1990) <doi:10.1038/344734a0>, the S-map algorithm from Sugihara (1994) <doi:10.1098/rsta.1994.0106>, convergent cross mapping described in Sugihara et al. (2012) <doi:10.1126/science.1227079>, and, multiview embedding described in Ye & Sugihara (2016) <doi:10.1126/science.aag0863>.
Note: Version 1.0 is a major rewrite of the 'rEDM' package as a wrapper
for the 'cppEDM' library.  Function names and signatures have
changed.  This allows a unified computation engine for EDM
algorithms across C++, Python and R implementations.  The
'cppEDM' is written in a functional programming paradigm,
facilitating clarity and ease of understanding to foster
collaboration and extension.  The revised package provides
improved alignment between observed and forecast data rows,
and, strict exclusion of partial data vectors.  Gaussian
process regression is not currently implemented.
Author: Joseph Park [aut, cre] (ORCID:0000-0001-5411-1409),