Innovative statistical methods for analysing high-dimensional counts

用于分析高维计数的创新统计方法

• 批准号: DP210101923
• 负责人: Prof David Warton
• 金额: $ 28.84万
• 依托单位: The University of New South Wales
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2021
• 资助国家: 澳大利亚
• 起止时间: 2021-08-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP210101923
• 关键词: Innovative; statistical; methods; analysing; dimensional

The aim is to develop fast, modern statistical methods for analysing high dimensional data in ecology at large scales, in particular, for visualising, classifying and predicting ecological communities. The benefit of the project is a set of multivariate tools that can be used to better understand biodiversity and its response to environmental drivers, a challenging statistical problem. The proposed methods for analysing high dimensional data can provide insight into large scale questions in ecology, such as automated identification of biogeographic boundaries. The expected outcome is a powerful statistical toolset for model-based analysis of high dimensional data, introducing modern multivariate approaches to a high-impact area of ecology.

其目的是开发快速，现代化的统计方法，用于分析大尺度生态学中的高维数据，特别是用于可视化，分类和预测生态群落。该项目的好处是一套多元工具，可用于更好地了解生物多样性及其对环境驱动因素的反应，这是一个具有挑战性的统计问题。所提出的方法分析高维数据可以提供洞察生态学中的大规模问题，如自动识别地理边界。预期的结果是一个强大的基于模型的高维数据分析的统计工具集，引入现代多元方法的生态高影响区。