logistic_map_fourspecies_transitive: Four-species logistic map system. Transitive unidirectional...

In kahaaga/chaoticmaps:

Description

Source: Ye, H. et al. (2015). Distinguishing time-delayed causal interactions using convergent cross mapping. Sci. Rep. 5, 14750; doi: 10.1038/srep14750 (2015)

Usage

logistic_map_fourspecies_transitive(n = 3000, y1.i = 0.4, y2.i = 0.4,
  y3.i = 0.4, y4.i = 0.4, Ry1y1 = 3.9, Ry1y2 = 0.4, Ry2y2 = 3.6,
  Ry2y3 = 0.4, Ry3y3 = 3.6, Ry3y4 = 0.35, Ry4y4 = 3.8,
  add.timestep = FALSE, plot = FALSE)

Arguments

n	The number of time steps that will be generated.
y1.i	Initial value of time series y1.
y2.i	Initial value of time series y2.
y3.i	Initial value of time series y3.
y4.i	Initial value of time series y4.
Ry1y1	Parameter controlling the influence of y1 at timestep i on itself at timestep i+1
Ry1y2	Parameter controlling the influence of y1 at timestep i on y2 at timestep i+1
Ry2y2	Parameter controlling the influence of y2 at timestep i on itself at timestep i+1
Ry2y3	Parameter controlling the influence of y2 at timestep i on y3 at timestep i+1
Ry3y3	Parameter controlling the influence of y1 at timestep i on itself at timestep i+1
Ry3y4	Parameter controlling the influence of y3 at timestep i on y4 at timestep i+1
Ry4y4	Parameter controlling the influence of y1 at timestep i on itself at timestep i+1

Details

This function allows you to express your love of cats.

Value

A dataframe containing columns time series for y1, y2, y3 and y4 (and optionally "t", a timestep column).

Defaults values are as in the original paper.

kahaaga/chaoticmaps documentation built on May 31, 2019, 1:16 p.m.