## Goals

- Detection and description of typical signatures of time series (periods, scaling exponents, dependencies)
- Prediction (e.g. weather forecasting)
- Modelling of time series (e.g. parameter estimation for the equation of motion)

Time series arise in each scientific discipline as soon as the temporal development is regarded. Time series represent the temporal sequence of states (e.g. climate, position or brightness of a star, heart rate, fever curve, stock exchange courses, account movements).

- Detection and description of typical signatures of time series (periods, scaling exponents, dependencies)
- Prediction (e.g. weather forecasting)
- Modelling of time series (e.g. parameter estimation for the equation of motion)

- Stationarity
- Measures of complexity and symbolic dynamics
- Recurrence plots
- Wavelet analysis
- Dimension density
- Cluster analysis
- Synchronization analysis
- ACE and nonlinear regression
- Estimation of model parameters (unscented Kalman filter)
- Forecasting
- Surrogate data

collection of many tools in TOCSY