Autocorrelation and Time Series Analysis

Abstract

In several disciplines time series analysis is of increasing importance. It is used (1) in a number of applications:

• Optimal forecast, i.e. the estimation of future values of the known current and past values of the series up to the present time.

• Parameter estimation, i.e. the estimation of system parameters from time series (signals) generated during a measurement procedure.

• Transfer function estimation. A transfer function typifies the inertial characteristics of a linear system.

• Information extraction, i.e. the extraction of relevant information from time series containing much more but not relevant information. The separation of signal and noise (noise reduction, filtering, signal estimation) belongs to this category.

• Optimal control. A time series of (analytical) results can be used for optimum process control.