Advanced Mixture Models for the Analysis of Modern-Day Data

用于分析现代数据的高级混合模型

• 批准号: DP140103423
• 负责人: Prof Geoffrey McLachlan
• 金额: $ 33.08万
• 依托单位: The University of Queensland
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2014
• 资助国家: 澳大利亚
• 起止时间: 2014-01-01 至 2017-09-29
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP140103423
• 关键词: Advanced; Mixture; Models; Analysis; Modern

Extracting key information from huge data sets is critical to the scientific successes of the future. This project will develop novel mixture models that can be used directly to analyse complex and high-dimensional data sets that may consist of thousands of variables observed on only a limited number of entities. In order to handle the challenging problems arising in the latter situation. This project develops mixtures of factor models with options for skew distributions that can be used to effectively analyse such data. Key applications include the domains of bioinformatics, biostatistics, business, data mining, economics, finance, image analysis, marketing, and personalised medicine, among many others.

从庞大的数据集中提取关键信息对于未来的科学成功至关重要。该项目将开发新的混合模型，可直接用于分析复杂的高维数据集，这些数据集可能由仅在有限数量的实体上观察到的数千个变量组成。为了处理后一种情况下出现的具有挑战性的问题。该项目开发了具有偏态分布选项的混合因子模型，可用于有效分析此类数据。主要应用包括生物信息学，生物统计学，商业，数据挖掘，经济学，金融，图像分析，市场营销和个性化医疗等领域。