Nonparametric change-point analysis, invariance principles for multivariate Student processes, and asymptotic theory in linear errors-in-variables models

非参数变点分析、多元学生过程的不变原理以及线性变量误差模型中的渐近理论

• 批准号: RGPIN-2018-05052
• 负责人: Martsynyuk, Yuliya
• 金额: $ 1.46万
• 依托单位: University of Manitoba
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=736152
• 关键词: Nonparametric; change; point; analysis; invariance

Asymptotic normality of the multivariate Student t-statistic; Asymptotics for LSE's and LSP's in linear EIVM's; Detection of at most one change in the mean; Detection of change in the slope and intercept in EIVM's; Infinite variances data in linear EIVM's; Invariance principles for multivariate Student processes; Least squares estimators/processes (LSE/LSP) in linear EIVMs; Linear errors-in-variables models (EIVM); Nonparametric change-point analysis; Self-normalized partial sums processes

多元Student t统计量的渐近正态性;线性EIVM中LSE和LSP的渐近性;最多一次均值变化的检测; EIVM中斜率和截距变化的检测;线性EIVM中的无穷方差数据;多元Student过程的不变性原理;线性EIVM中的最小二乘估计/过程（LSE/LSP）;线性变量误差模型（EIVM）;非参数变点分析;自正规化部分和过程