Time Series (Authors Michael Hauser and Wolfgang Hörmann)
In this chapter we are concerned with times series, i.e. with the generation of sample paths of stochastic non-deterministic processes in discrete time, (X t ,t ∈ ℤ), where X t are continuous random variates. In the first part we will focus our presentation on stationary Gaussian processes. These are most widely used in the analysis of, e.g., economic series or in signal processing.
KeywordsCovariance Expense Autocorrelation Convolution Tral
Unable to display preview. Download preview PDF.