stateSpace: State Space Reconstruction

In patterncausality: Pattern Causality Algorithm

State Space Reconstruction

Description

Reconstructs the state space of a time series using delay embedding, creating a matrix where each row represents a point in the reconstructed space.

Usage

stateSpace(ts, E, tau, verbose = FALSE)

Arguments

ts	Numeric vector; time series data
E	Integer; embedding dimension (E > 1)
tau	Integer; time delay (tau > 0)
verbose	Logical; whether to display progress information

Details

State Space Reconstruction Analysis

The function implements Takens' embedding theorem to reconstruct state space:

• Creates delay vectors using specified embedding dimension (E)

• Applies time delay (tau) between consecutive elements

• Handles boundary conditions and missing values

Value

An object of class "pc_state" containing:

• matrix: The reconstructed state space matrix

• parameters: List of reconstruction parameters

• original: Original time series data

Related Packages

• nonlinearTseries: Nonlinear time series analysis

• tseriesChaos: Chaos theory analysis tools

• fractal: Fractal analysis methods

Examples

ts <- c(1:100)
result <- stateSpace(ts, E = 3, tau = 2)
plot(result)

patterncausality documentation built on April 3, 2025, 6:57 p.m.