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tseriesChaos is an R package for the analysis of nonlinear time series mainly motivated by chaos theory.

You can install from a CRAN mirror near you by typing, at the R prompt:

> install.packages('tseriesChaos', dep=TRUE)

Its developement was initially inspired by the TISEAN project.

Currently, the 0.1-7 version is out, and mainly includes explorative methods. Among others:

  • Kantz method for Maximal Lyapunov Exponent (MLE) estimation
  • efficient correlation integral computation for estimating fractal dimension
  • false nearest neighbours
  • space-time separation plots
  • recurrence plots
  • grid-based average mutual information computation

Forthcoming

A new, completely revised and extended version of the package supported by the PRIN project coordinated by Estela Bee Dagum, Statistics Department, University of Bologna.

The new version will include:

  • Statistical tests for chaos based on Lyapunov exponents estimation with different methods available:
    1. Kantz method, resampled version (Giannerini and Rosa, Physica D (2001));
    2. Neural Network, asymptotic version (Shintani and Linton, J. Econometrics (2005));
  • Local Lyapunov exponents estimation
  • Extension to the stochastic case of Lyapunov Exponents: measures of sensitivity to initial conditions of the conditional mean (Yao and Tong JRSS B (1994)) and of the conditional distribution (Fan, Yao and Tong, Biometrika (1996)), see also Giannerini and Rosa SNDE (2004).
  • Entropy based tests for nonlinearity (Granger, Maasoumi & Racine JTSA 2004, Giannerini, Maasoumi & Bee Dagum forthcoming).
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