two_species_model

Time series generated from a discrete-time coupled 
 Lotka-Volterra model exhibiting chaotic dynamics.

datasets

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>.

Sugihara Maintainer

rEDM

Applications of Empirical Dynamic Modeling from Time Series

Hao Ye

Adam Clark

Ethan Deyle

Steve Munch

Jun Cai

Jane Cowles

Yair Daon

Andrew Edwards

Os Keyes

James Stagge

Masayuki Ushio

Ethan White

Takeshi Abe

George Sugihara

two_species_model function

A data frame with 1000 rows and 3 variables:<dl class="dl-horizontal">
 <dt><code>time</code></dt><dd>time index (# of generations)</dd>
 <dt><code>x</code></dt><dd>abundance of simulated species x</dd>
 <dt><code>y</code></dt><dd>abundance of simulated species y</dd>
</dl>

Format

Time series for a two-species coupled model. — two_species_model

A data frame with 1000 rows and 3 variables:<dl class='dl-horizontal'>
 <dt><code>time</code></dt><dd>time index (# of generations)</dd>
 <dt><code>x</code></dt><dd>abundance of simulated species x</dd>
 <dt><code>y</code></dt><dd>abundance of simulated species y</dd>
</dl>

Time series for a two-species coupled model.

two_species_model: Time series for a two-species coupled model.

Description

Usage

Arguments

Format