Statistical Modelling in the Era of Data Science: Theory and Practice

数据科学时代的统计建模：理论与实践

• 批准号: FT190100374
• 负责人: Prof Howard Bondell
• 金额: $ 50.31万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: ARC Future Fellowships
• 财政年份: 2020
• 资助国家: 澳大利亚
• 起止时间: 2020-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FT190100374
• 关键词: Statistical; Modelling; Era; Data; Science

This project aims to develop innovative statistical methodology that is interpretable, theoretically justified, and scalable to today's growing complex data. With the influx of data being collected in both the public and private sectors, making sense of this data is a fundamental task. Through a rigorous modelling framework, this project intends to facilitate the discovery of knowledge by developing powerful new tools to extract insight from these complex datasets. The outcomes of this project will benefit society by providing techniques to enable research advances and inform decision-making for a broad base of disciplines, including applications to network security, energy forecasting, environmental monitoring, and public health.

该项目旨在开发创新的统计方法，该方法可解释，理论上合理，并可扩展到当今日益复杂的数据。随着公共和私营部门收集的数据大量涌入，理解这些数据是一项基本任务。通过严格的建模框架，该项目旨在通过开发强大的新工具来从这些复杂的数据集中提取洞察力，从而促进知识的发现。该项目的成果将通过提供技术来促进研究进展，并为广泛的学科基础提供决策信息，包括网络安全、能源预测、环境监测和公共卫生方面的应用，从而造福社会。