Japanese Journal of Statistics and Data Science - Call for Papers on "Advanced Theory and Applications in Time Series Analysis"
Coordinating Editors: Cathy W. S. Chen (Feng Chia University, Taiwan) and Manabu Asai (Soka University, Japan)
Due Date: June 30, 2025
Intended Publication Date: June 1, 2026
Description:
Time series analysis stands at the forefront of statistical and econometric research, offering powerful tools to analyze and interpret data evolving over time. It has found pervasive applications across diverse fields such as economics, finance, environmental science, engineering, and beyond. As the complexity and volume of time series data continue to grow exponentially, there is an increasing demand for innovative methodologies that can uncover hidden patterns, improve forecasting accuracy, and facilitate decision-making in both academia and industry.
This special issue aims to showcase the latest advancements in time series analysis, providing a platform for researchers to disseminate their novel contributions to the field. We seek submissions that delve into theoretical developments, methodological innovations, and practical applications of time series models. Topics of interest include but are not limited to advanced modeling techniques, high-dimensional data analysis, non-linear dynamics, machine learning approaches, Bayesian inference, and forecasting methodologies.
Topics of interest for this issue include but are not limited to:
- Advanced time series models and methodologies
- Nonlinear time series analysis
- High-dimensional time series
- Forecasting and predictive analytics
- Time series in finance, economics, and business
- Big data approaches in time series analysis
- LASSO techniques for time series data
- Time series analysis in climate science and environmental studies
- Time series analysis in healthcare and epidemiology
- Signal processing and time series analysis
- Bayesian approaches to time series modeling
- Time series clustering and classification
- Latent variable models for time series data
- Modeling time series of counts
Papers must be submitted to the journal's submission system. Please select “Yes” for the question “Does this manuscript belong to a special feature?” and then select the special feature “S.I. : Advanced Theory and Applications in Time Series Analysis”.