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We review the past 25 years of research into time series forecasting. In this silver jubilee issue, we naturally highlight results published in journals ...

Time-series forecasting is based on the assumption that future values of the series can be estimated from past values (e.g. Stevenson, 2012). If there is ample ...

The Journal of Time Series Analysis is the leading mathematical statistics journal focused on the important field of time series analysis and its ...

Jan 9, 2024 · Time-series forecasting is a practical goal in many areas of science and engineering. Common approaches for forecasting future events often ...

We describe two automatic forecasting algorithms that have been implemented in the forecast package for R. The first is based on innovations state space models ...

Feb 15, 2021 · In this article, we summarize the common approaches to time-series prediction using deep neural networks. Firstly, we describe the state-of-the- ...

1. Introduction. Time series forecasting (TSF) is a field of study that involves all aspects of society, and the concept has been around for decades in ...

This special issue aims to bring together the latest advances, innovations, and research in the field of time series forecasting.

Apr 16, 2024 · In this paper, we study the existing econometric models for time series and machine learning models and classify them based on their ...