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Computer Intensive Methods in Sampling and in Adaptive Contexts

Computer Intensive Methods in Sampling and in Adaptive Contexts
采样和自适应环境中的计算机密集型方法
批准号:
RGPIN-2016-05686
负责人:
Léger, Christian
金额:
$1.09万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31

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中文摘要
翻译
快速计算使统计学家能够开发出新的统计方法,这在以前是不可想象的,因为它们不可能在实践中使用。Bootstrap就是一个例子。它可用于计算复杂估计量的方差估计或构造置信度区间。这一研究方案的主要目标是提高对这些方法的理论和实践理解,以制定健全的新统计程序。
英文摘要
Fast computing has allowed statisticians to develop new statistical methods that would have been unthinkable before due to the impossibility to use them in practice. One example is the bootstrap. It can be used to compute variance estimates for complicated estimators or construct confidence intervals. The main goal of this research program is to improve the theoretical and practical understanding of these methods to develop sound new statistical procedures.
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Computer Intensive Methods in Sampling and in Adaptive Contexts
  • 批准号:
    RGPIN-2016-05686
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.19万
  • 财政年份:
    2022
  • 负责人:
    Léger, Christian
  • 依托单位:
Computer Intensive Methods in Sampling and in Adaptive Contexts
  • 批准号:
    RGPIN-2016-05686
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.09万
  • 财政年份:
    2019
  • 负责人:
    Léger, Christian
  • 依托单位:
Computer Intensive Methods in Sampling and in Adaptive Contexts
  • 批准号:
    RGPIN-2016-05686
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.09万
  • 财政年份:
    2018
  • 负责人:
    Léger, Christian
  • 依托单位:
Computer Intensive Methods in Sampling and in Adaptive Contexts
  • 批准号:
    RGPIN-2016-05686
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.09万
  • 财政年份:
    2016
  • 负责人:
    Léger, Christian
  • 依托单位:
海外基金