New Directions in Bayesian Statistics: formulation, computation and application to exemplar challenges

贝叶斯统计的新方向：示例挑战的公式、计算和应用

• 批准号: DP140103564
• 负责人: Prof Kerrie Mengersen
• 金额: $ 15.94万
• 依托单位: Queensland University of Technology
• 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 2015-12-09
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP140103564
• 关键词: New; Directions; Bayesian; Statistics; formulation

Bayesian statistics is a fundamental statistical and machine learning approach for density estimation, data analysis and inference. However, there remain open questions regarding the formulation of the model, the likelihood and priors, and efficient computation. This project proposes new approaches that address these issues, and applies them to two exemplar challenges: the impact of climate change on the Great Barrier Reef and better understanding neurological diseases related aging, in particular Parkinson's Disease.

贝叶斯统计是一种用于密度估计、数据分析和推理的基本统计和机器学习方法。然而，关于模型的制定、可能性和先验以及高效计算仍然存在悬而未决的问题。该项目提出了解决这些问题的新方法，并将其应用于两个典型挑战：气候变化对大堡礁的影响以及更好地了解与衰老相关的神经系统疾病，特别是帕金森病。