Many real phenomena exhibit non-Gaussian behavior. The non-Gaussianity is mainly
manifested by impulsive behavior of the real signals that, typically is not visible in the …

Correlation and spectral analysis represent the standard tools to study interdependence in
statistical data. However, for the stochastic processes with heavy-tailed distributions such …

This paper discusses the problem of parameters estimation for stable periodic
autoregressive (PAR) time series. Considered models generalize popular and widely …

In this paper, we consider the problem of a measure that allows us to describe the spatial
and temporal dependence structure of multivariate time series with innovations having …

This paper tests the null hypothesis of stationarity against the alternative of changes in
persistence for sequences in the domain of attraction of a stable law. The proposed moving …

Measuring the dependency between lagged random vectors in time series is extremely
important to detect appropriate models for fitting real data. Vector autoregressive processes …

Local damage detection in rotating machinery is simply searching for cyclic impulsive signal
in noisy observation. Such raw signal is mixture of various components with specific …

Many real phenomena exhibit non‐Gaussian behavior. The non‐Gaussianity is manifested
by impulsive behavior of the real data that can be found in both one‐dimensional and multi …

Many real data exhibit behavior adequate to subdiffusion processes. Very often it is
manifested by so-called “trapping events”. The visible evidence of subdiffusion we observe …

In this paper, we consider a bidimensional autoregressive model of order 1 with $\alpha-$
stable noise. Since in this case the classical measure of dependence known as the …