Robust and Nonlinear Time Series Analysis
Franke, J. / Martin, D. / Härdle, W.![Robust and Nonlinear Time Series Analysis](https://support.digitalhusky.com/media/annotations/sorted/110/11012504/CHSBZCOP0311012504.jpg)
Classical time series methods are based on the assumption that a particular stochastic process model generates the observed data. The, most commonly used assumption is that the data is a realization of a stationary Gaussian process. However, since the Gaussian assumption is a fairly stringent one, this assumption is frequently replaced by the weaker assumption that the process is wide~sense stationary and that only the mean and covariance sequ...