The Journal of Time Series Analysis is the leading mathematical statistics journal focused on the important field of time series analysis.
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This paper provides a selective guide to the literature on time series forecasting, covering the period 1982–2005 and summarizing over 940 papers.
Time series forecasting is one of the most widely used applications of data science. This chapter provides a comprehensive overview of time series analysis and ...
Feb 15, 2021 · In this article, we survey common encoder and decoder designs used in both one-step-ahead and multi-horizon time-series forecasting.
The Journal of Time Series Analysis is the leading mathematical statistics journal focused on the important field of time series analysis and its ...
We describe two automatic forecasting algorithms that have been implemented in the forecast package for R.
Jul 3, 2024 · In this paper, our objectives are to introduce and review methodologies for modeling time series data, outline the commonly used time series forecasting ...
Jan 9, 2024 · Time-series forecasting is a practical goal in many areas of science and engineering. Common approaches for forecasting future events often ...
May 14, 2024 · In this paper, we introduce a novel method to improve the performance of deep learning models in 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 characteristics.
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