Handling Time in Environmental Studies
Organiser
Participants
Conference
Category: Women in Statistics
Proposal Description
The analysis of environmental data often presents challenges, including limited detection thresholds, missing data, image analysis, restricted measurement domains, outliers, autocorrelation, and spatial correlation. This section aims to present and illustrate modern solutions for such problems, focusing on temporal-dependent environmental data. Through theoretical discussions, methodological proposals, and case studies, the section will provide valuable perspectives for researchers in environmental science, ecology, climate studies, and related fields. It aims to provide tools for modeling complex environmental processes and dynamics by effectively leveraging temporal data analysis techniques under a variety of scenarios.
Submissions
- Autoregressive moving average model based on the Reflect Unit Burr XII distribution: theory and applications in hydroelectric energy forecasting
- Censored autoregressive regression models with Student-t innovations and their application in river water quality assessment
- Longitudinal data under antedependence model with applications to environmental sciences
- Spatio-temporal survival analysis: application to environmental data