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Asymptotic inference based on likelihood function

Asymptotic inference based on likelihood function
基于似然函数的渐近推理
批准号:
159996-2007
负责人:
Wong, Augustine
金额:
$1.38万
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:
2008
资助国家:
加拿大
项目状态:
已结题
起止时间:
2008-01-01 至 2009-12-31

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中文摘要
翻译
在实践中,关于感兴趣的标量参数的推理通常是使用一阶渐近方法来实现的。然而,当样本量较小时,这些方法可能会给出误导性的推断。近年来,高阶渐近方法得到了广泛的研究。不管高阶方法的极端精度(就尾部概率近似而言),它们并不受欢迎,因为这些方法的“可访问性”有限。本文的第一个目的是将高阶方法应用于一些常用的参数模型的标准统计和代数软件,如R、sPlus、Maple和MatLab。
英文摘要
In practice, inference concerning a scalar parameter of interest generally is achieved by using first-order asymptotic methods. These methods, however, can give misleading inference when the sample size is small. In recent years, higher-order asymptotic methods have been studied extensively. Regardless of the extreme accuracy (in terms of tail probability approximations) of the higher-order methods, they are not popular because of the limited "accessibility" of these methods. The first aim of this propoal is to implement the higher-order methos to some standard statistical and algebraic softwares such as R, Splus, Maple, and Matlab for some commonly used parametric models.
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Statistical inference with applications
  • 批准号:
    RGPIN-2017-05719
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.17万
  • 财政年份:
    2022
  • 负责人:
    Wong, Augustine
  • 依托单位:
Statistical inference with applications
  • 批准号:
    RGPIN-2017-05719
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.17万
  • 财政年份:
    2021
  • 负责人:
    Wong, Augustine
  • 依托单位:
Statistical inference with applications
  • 批准号:
    RGPIN-2017-05719
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.17万
  • 财政年份:
    2020
  • 负责人:
    Wong, Augustine
  • 依托单位:
Statistical inference with applications
  • 批准号:
    RGPIN-2017-05719
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.17万
  • 财政年份:
    2019
  • 负责人:
    Wong, Augustine
  • 依托单位:
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