In order to analyse surface electromyography (EMG) signals, it is necessary to extract the features based on a time or frequency domain. These approaches are based on the mathematical assumption of signal stationarity. Stationarity of EMG signals is thoroughly examined, especially in isotonic contractions. According to research, conflicting results have been identified depending on varying wind...

Tests of stationarity are routinely applied to highly autocorrelated time series. Following Kwiatkowski et al. (J. Econom. 54 (1992) 159), standard stationarity tests employ a rescaling by an estimator of the long-run variance of the (potentially) stationary series. This paper analytically investigates the size and power properties of such tests when the series are strongly autocorrelated in a ...

The effect of the single currency on the Purchasing Power Parity (PPP) hypothesis is examined in this study for the 15 EU countries, vis a vis the US dollar, before and after the advent of the euro. Standard as well as nonlinear unit root tests are employed on the time series dimension. Unit root tests reject PPP and the highest half-lives are observed after the introduction of the single curre...

Most methods used in the field of linear and nonlinear time series analysis assume stationarity of the considered data. Non–stationarity is very likely to lead to wrong results. This is especially true for tests for nonlinearity. A common approach is to split the time series into segments which can be considered nearly stationary and perform individual tests. But for short time series or not to...

To derive tests for randomness, nonlinear-independence, and stationarity, we combine surrogates with a nonlinear prediction error, a nonlinear interdependence measure, and linear variability measures, respectively. We apply these tests to intracranial electroencephalographic recordings (EEG) from patients suffering from pharmacoresistant focal-onset epilepsy. These recordings had been performed...

One of the most important hydrological time series task is to determine if there is any trend in the data and how to achieve stationarity when there is nonstationarity behavior in data. Detecting trend and stationarity in hydrological time series may help us to understand the possible links between hydrological processes and global climate changes. In this study yearly, monthly and daily stream...