Methods of dimension reduction are very helpful and almost a necessity if we want to analyze high-dimensional time series since otherwise modelling affords many parameters because of interactions at various time-lags. We use a dynamic version of Sliced Inverse Regression (SIR; Li (1991)), which...

We investigate the possibility of exploiting partial correlation graphs for identifying interpretable latent variables underlying a multivariate time series. It is shown how the collapsibility and separation properties of partial correlation graphs can be used to understand the relation between...

Two different estimation techniques for the spectrum of a nonstationary time series are compared empirically. Both of them are assuming a time-dependent autoregressive (AR-) model for the data. The first estimation technique used is the Frequency State Dependent Model (FSDM-) technique (Schmitz...

In the present study we investigate the data provided by the karstwater level monitoring system set up in the Transdanubian Mountains, more precisely in the Bakony, the Keszthelyi Mountains and the Balaton-Highland. (Here, like in the sequel, the term karstwater is used for groundwater in...