Chaotic Time Series Analysis
Description
Chaos theory has been hailed as a revolution of thoughts and attracting ever increasing
attention of many scientists from diverse disciplines. Chaotic systems are nonlinear deterministic
dynamic systems which can behave like an erratic and apparently random motion. A relevant field
inside chaos theory and nonlinear time series analysis is the detection of a chaotic behaviour
from empirical time series data. One of the main features of chaos is the well known initial value
sensitivity property. Methods and techniques related to test the hypothesis of chaos try to quantify
the initial value sensitive property estimating the Lyapunov exponents. The DChaos package
provides different useful tools and efficient algorithms which test robustly the hypothesis of chaos
based on the Lyapunov exponent in order to know if the data generating process behind time series
behave chaotically or not.