Coronavirus disease-19 (COVID-19) emerged in December 2019 and quickly spread, giving
rise to a pandemic crisis. Therefore, it triggered tireless efforts to identify the mechanisms of …

The coronavirus disease 2019 (COVID-19) pandemic induced a sudden surge in COVID-19
related publications. This bibliometric analysis aimed to analyze literature on physical …

This paper describes one of the non-linear (and non-stationary) stochastic models, the GSB
(Gaussian, or Generalized, Split-BREAK) process, which is used in the analysis of time …

The nonlinear progression of COVID-19 positive cases, their fluctuations, the correlations in
amplitudes and phases across different regions, along with seasonality or periodicity, pose …

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused the
Coronavirus Disease (COVID-19) pandemic worldwide. The spike protein in SARS-CoV-2 …

The chaos theory, a field of study in mathematics and physics, offers a unique lens through
which to understand the dynamics of the COVID-19 pandemic. This theory, which deals with …

Zero-and-one inflated count time series have only recently become the subject of more
extensive interest and research. One of the possible approaches is represented by first …

Background In this work, we implement a data-driven approach using an aggregation of
several analytical methods to study the characteristics of COVID-19 daily infection and death …

Background Recent studies applying chaos theory methods have found the existence of
chaotic markers in SARS-CoV-2's epidemiological data, evidence that has implications on …

This manuscript deals with a parameter estimation of a non-negative integer-valued (NNIV)
time series based on the so-called probability generating function (PGF) method. The …