Tentative Program

This track focuses on innovative methodologies for analyzing time series data, including both classical and contemporary approaches. Participants will explore techniques such as ARIMA, GARCH, and state-space models to enhance forecasting accuracy.

This session will delve into the development and application of probabilistic forecasting models across various domains. Emphasis will be placed on uncertainty quantification and the integration of probabilistic approaches in forecasting frameworks.

This track aims to bridge the gap between theoretical statistical modeling and practical applications in diverse fields. Attendees will share case studies that highlight the impact of statistical models on real-world decision-making.

This session will cover the role of simulation methods in statistical analysis, including Monte Carlo simulations and bootstrapping techniques. Participants will learn how to apply these methods to enhance inference and model validation.

This track focuses on the application of statistical methods in various industries, including finance, healthcare, and manufacturing. It will showcase how statistical analysis drives innovation and efficiency in real-world scenarios.

This session will explore advanced regression techniques and their applications in predictive modeling. Participants will discuss the nuances of linear and nonlinear regression, as well as regularization methods.