With the increasing demand of passenger and freight air transportation and their key role in
energy consumptions, this study developed a hybrid framework integrating machine …

In recent years, the surge of unofficial digital currencies, often referred to as
cryptocurrencies, has disrupted traditional financial landscapes. Bitcoin, being the most …

Both locally stationary processes and irregular models have had a long story of success in
statistics and time series analysis. We combine both concepts and consider a …

This paper proposes a first-order geometric autoregressive model based on a new thinning
operator. The parameters of the model are estimated by the method of Two-Stage …

A test statistic for nonlinearity of a given heavy-tailed time series process is constructed,
based on the sub-sample stability of Gini-based sample autocorrelations. The finite-sample …

This paper proposes a method for analyzing count time series with inflation or deflation of
zeros. In particular, zero-modified Poisson and zero-modified negative binomial series with …

We propose a new method to construct a stationary process and random field with a given
decreasing covariance function and any one-dimensional marginal distribution. The result is …

A stationary sequence of nonnegative random variables generated by autoregressive (AR)
models may be used to describe the inter‐arrival times between events in counting …

In financial modeling, the assumption of Gaussian noise, has been a classical assumption.
Models based on this assumption have been widely used in various fields due to their …

This paper analyses a stochastic volatility model generated by first order normal-Laplace
autoregressive process. The model parameters are estimated by the generalized method of …