A random walk through Canadian contributions on empirical processes and their applications in probability and statistics

被引:0
|
作者
Csorg, Miklos [1 ]
Dawson, Donald A. [1 ]
Nasri, Bouchra R. [2 ]
Remillard, Bruno N. [3 ]
机构
[1] Carleton Univ, Sch Math & Stat, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada
[2] Univ Montreal, Dept Med Sociale & Prevent, Ecole Sante Publ, CP 6128,Succursale Ctr Ville Montreal, Montreal, PQ H3C 3J7, Canada
[3] HEC Montreal, Dept Decis Sci, 3000 Chemin Cote St Catherine, Montreal, PQ H3T 2A7, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Change point; copulas; empirical process; Fleming-Viot; generalized error models; goodness-of-fit; McKean-Vlasov; measure-valued process; strong approximation; super Brownian motion; time series; STRASSEN TYPE LAWS; OF-FIT TESTS; STRONG APPROXIMATIONS; ASYMPTOTIC OPTIMALITY; SERIAL INDEPENDENCE; WEAK-CONVERGENCE; MARKOV-PROCESSES; FISHERS METHOD; PARTIAL SUMS; MULTIVARIATE;
D O I
10.1002/cjs.11730
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this article, we present a review of important results and statistical applications obtained or generalized by Canadian pioneers and their collaborators, for empirical processes of independent and identically distributed observations, pseudo-observations, and time series. In particular, we consider weak convergence and strong approximations results, as well as tests for model adequacy such as tests of independence, tests of goodness-of-fit, tests of change point, and tests of serial dependence for time series. We also consider applications of empirical processes of interacting particle systems for the approximation of measure-valued processes.
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页码:1116 / 1142
页数:27
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