In this paper, we consider a variety of multi-state hidden Markov models for predicting and
explaining the Bitcoin, Ether and Ripple returns in the presence of state (regime) dynamics …

An hourly water temperature time series recorded at the Gairn catchment (Scotland) is
analysed here along with seven covariates. Modelling river temperature time series is …

This study examines a new approach for short‐term wind speed and power forecasting
based on the mixture of Gaussian hidden Markov models (MoG‐HMMs). The proposed …

It is generally believed that intelligent management for sewage treatment plants (STPs) is
essential to the sustainable engineering of future smart cities. The core of management lies …

Markov switching models are a popular family of models that introduces time-variation in the
parameters in the form of their state-or regime-specific values. Importantly, this time-variation …

We study the Bitcoin and Ether price series under a financial perspective. Specifically, we
use two econometric models to perform a two-layer analysis to study the correlation and …

With Bitcoin, Ether and more than 2000 cryptocurrencies already forming a multi-billion
dollar market, a proper understanding of their statistical and financial properties still remains …

Recent advances in imaging technologies now allow for real-time tracking of fast-moving
immune cells as they search for targets such as pathogens and tumor cells through complex …

This article aims to investigate the relationship between the available past and desired
prediction spans of the compositional time series (CTS) data, while comparatively analyzing …

In this paper, we conduct a thorough investigation of the predictive ability of forward and
backward stepwise regressions and hidden Markov models for the futures returns of several …