Scope of Submission
We welcome submissions from a broad range of disciplines, including but not limited to:
- Time series forecasting techniques
- Stochastic modeling of time-dependent data
- Applications in financial time series analysis
- Seasonal patterns in time series data
- Statistical methods for time series analysis
- ARIMA models and their applications
- Longitudinal data analysis techniques
- Nonlinear time series modeling approaches
- Time series analysis in environmental studies
- Machine learning for time series prediction
- Causal inference in time series data
- Time series analysis in healthcare
- Multivariate time series modeling techniques
- Applications in signal processing
- Real-time analysis of streaming data
- Time series anomaly detection methods
- Bayesian approaches to time series
- Time series analysis in social sciences
- Forecasting with exogenous variables
- Applications in supply chain management
All papers must be original and not previously published or submitted elsewhere.
