The article focuses on properties generalised to the multidimensional case of known coefficients of spatial correlation. The main result of the work is the decomposition of the introduced generalised autocorrelation coefficients into the sum of ordinary autocorrelation coefficients, but...

This paper presents a novel copula-based autoregressive framework for multilayer arrays of integer-valued time series with tensor structure. It complements recent advances in tensor time series that predominantly focus on real-valued data and overlook the unique properties of integer-valued time...

The multivariate Vasicek model is commonly used to capture mean-reverting dynamics typical for short rates, asset price stochastic log-volatilities, etc. Reparametrizing the discretized problem as a VAR(1) model, the parameters are oftentimes estimated using the multivariate least squares (MLS)...

Research background: The unadjusted gender pay gap (GPG) is one of the indicators that measure progress towards SDG5. There is considerable variability in the values of this indicator among the individual countries and regions of the EU. However, due to the effects resulting from the...

This paper considers nonparametric estimation and inference in first-order autoregressive (AR(1)) models with deterministically time-varying parameters. A key feature of the proposed approach is to allow for time-varying stationarity in some time periods, time-varying nonstationarity (i.e., unit...

The presence of autocorrelated financial returns has major implications for investment decisions. Unsurprisingly, therefore, numerous studies have sought to shed light on whether returns are autocorrelated or not, to what extent, and when. Standard tests for autocorrelation rely on the...