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Call For Papers

The ICATSFM bridges the gap between academia and industry by promoting research with practical applications. It provides a platform for professionals and researchers to share insights that drive real-world impact.

The conference focuses on Statistics, Data Science, encouraging applied research, case studies, and industry-driven innovations.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Time series forecasting methods and applications
  • Statistical modeling of temporal data
  • Seasonal decomposition in time series analysis
  • ARIMA models for time series forecasting
  • Statistical methods for financial time series
  • Time series analysis in environmental studies
  • Machine learning techniques for time series
  • Statistical methods for anomaly detection in time series
  • Longitudinal data analysis techniques
  • Statistical software for time series analysis
  • Causal inference in time series data
  • Applications of time series in public health
  • Statistical challenges in high-frequency data
  • Time series regression modeling approaches
  • Forecasting with multivariate time series
  • Statistical methods for economic time series
  • Time series analysis in social sciences
  • Bayesian approaches to time series forecasting
  • Statistical techniques for real-time forecasting
  • Future directions in time series analysis

Evaluation

Submissions will be evaluated based on applicability, innovation, and research contribution. Accepted papers will be presented and considered for publication in relevant journals and proceedings.

Registration

Complete your registration to participate in discussions that bridge academia and industry, and gain exposure to practical insights.

Publication

Selected papers will be considered for publication platforms that support academic and industry collaboration.

Submit Your Paper Now Confirm Your Participation Today
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