channeled toward Yemen's economic reconstruction efforts. Design/methodology/approach - This study utilized a time-series …

distributional data as a time series of functions whose underlying factor structure follows a state-space model, which we estimate …

investment strategy based on signal indicators derived from news indices focusing on short-term trends using time-series …

This paper examines the use of machine learning methods in modeling and forecasting time series with long memory …-LSTM model outperforms traditional approaches in forecasting long-memory time series. This characteristic is confirmed using … accurate and reliable forecasting in long-memory time series. Additionally, we compare the GARMA-LSTM model with other …

channels, this paper builds a novel climate economy model using nonlinear model predictive control. Moreover, using time-series …

Accurately detecting anomalous points in time-series data is critical, as false positives can mislead business … theoretically and empirically on time-series datasets. Our findings demonstrate that the Ensemble Bayesian-aided approach …