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Statistical Inference

Statistical Inference
统计推断
批准号:
1000229172-2013
负责人:
Chen, Jiahua
金额:
$14.57万
依托单位国家:
加拿大
项目类别:
Canada Research Chairs
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31
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项目摘要

项目成果

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中文摘要
翻译
混合模型的统计方法可以梳理出关于总体子群特征的信息,甚至包括对现有子群数量的估计。这些方法在研究遗传多样性和确定疾病的遗传起源方面发挥了关键作用。由于混合模型的数学不规则性,开发有效的混合模型方法对许多有才华的统计学家提出了挑战。在此之前,我专注于这些挑战,从而成功开发了一系列强大的测试。我已经发表了几篇关于这些测试的论文,并得到了研究人员和从业者的积极反馈。
英文摘要
Statistical methods for mixture models can tease out information about the characteristics of population subgroups, even including estimation of the number of subgroups present. These methods play a key role in the study of genetic diversity and in pinpointing the genetic origins of disease. Development of effective methods for mixture models has challenged many talented statisticians, due to the mathematical irregularity of these models. Previously, I focused on these challenges, resulting in the successful development of a series of powerful tests. I have published several papers on these tests and have received positive feedback from both researchers and practitioners.
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会议论文
Theory and Applications of the empirical likelihood and finite mixture model
  • 批准号:
    RGPIN-2019-04204
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.62万
  • 财政年份:
    2022
  • 负责人:
    Chen, Jiahua
  • 依托单位:
Theory and Applications of the empirical likelihood and finite mixture model
  • 批准号:
    RGPIN-2019-04204
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.62万
  • 财政年份:
    2021
  • 负责人:
    Chen, Jiahua
  • 依托单位:
Statistical Inference
  • 批准号:
    1000229172-2013
  • 项目类别:
    Canada Research Chairs
  • 资助金额:
    $10.93万
  • 财政年份:
    2020
  • 负责人:
    Chen, Jiahua
  • 依托单位:
Theory and Applications of the empirical likelihood and finite mixture model
  • 批准号:
    RGPIN-2019-04204
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.62万
  • 财政年份:
    2020
  • 负责人:
    Chen, Jiahua
  • 依托单位:
海外基金