论文标题
基于计数过程的统计模型的教程
A Tutorial on Statistical Models Based on Counting Processes
论文作者
论文摘要
自1958年由Kaplan和Meier撰写的著名论文以来，生存分析已成为统计中最重要的领域之一。如今，它是分析包括COVID-19大流行在内的流行病学和临床数据的最重要的统计工具之一。本文在生存分析中回顾了一些最著名，最重要的结果和方法，包括一致性，渐近正态性，偏差和方差估计，并且治疗与基于计数过程的专着统计模型平行。还讨论了其他模型和结果，例如半马尔可夫模型以及特恩布尔的估计器，即跳出经典计数过程martingale框架。
Since the famous paper written by Kaplan and Meier in 1958, survival analysis has become one of the most important fields in statistics. Nowadays it is one of the most important statistical tools in analyzing epidemiological and clinical data including COVID-19 pandemic. This article reviews some of the most celebrated and important results and methods, including consistency, asymptotic normality, bias and variance estimation, in survival analysis and the treatment is parallel to the monograph Statistical Models Based on Counting Processes. Other models and results such as semi-Markov models and the Turnbull's estimator that jump out of the classical counting process martingale framework are also discussed.
