Proposal Description

This invited paper session, sponsored by the Latin American Regional Section of the International Association for Statistical Computing (LARS-IASC), brings together researchers from several IASC regions to present recent advances in statistical modelling and its applications. The session features contributions from speakers based in Brazil, Chile, Honduras, South Africa, and the United States, reflecting the international scope and collaborative spirit of the IASC-LARS community.

The presentations cover a broad range of contemporary topics, including high-dimensional volatility forecasting, multiblock data analysis, outlier and structural break detection in time series, robust methods for circular data, and classification techniques for multilevel multivariate data. Together, these contributions highlight methodological developments that address modern challenges arising from increasingly complex and high-dimensional datasets.

By showcasing innovative statistical methodologies and their practical applications, the session aims to foster collaboration among IASC regional sections and promote the exchange of ideas across different areas of statistical computing and data science. The topics presented are expected to be of interest to researchers, practitioners, and students working in statistics, data science, econometrics, and related disciplines.

Invited Talks:
Multiblock Data Analysis: Methods and Applications
Linear Classification with Multi-level Multivariate Data using Patterned Covariance Structure 
Forecasting High-Dimensional Volatility
Detecting Outliers and Structural Breaks in Time Series
Contamination models for robust analysis of circular data

The organizer will also serve as the session chair.