标题： 一种用于依赖性双截尾数据的柯尔莫哥洛夫-斯米尔诺夫型检验 显示英文标题

标题： A Kolmogorov-Smirnov-Type Test for Dependently Double-Truncated Data

摘要： 对于双截断寿命，我们检验寿命属于参数分布族的假设。人口统计学的典型发现是寿命期望的非平稳行为，而Copula模型则描述了寿命与截断年龄之间的弱依赖性。我们的主要例子是Farlie-Gumbel-Morgenstern Copula。该检验基于Donsker类论证和经验过程的函数delta方法。假设条件也允许参数推断，由于观测值的紧支撑，证明略有简化。给出了一个具有有限操作步骤的算法以计算检验统计量。为了计算临界值，需要进行模拟。以指数分布为例，并应用于55{,}000德国双截断企业寿命，构建的Kolmogorov-Smirnov检验明显拒绝了年龄同质闭合风险。 显示英文摘要

摘要： With double-truncated lifespans, we test the hypothesis of a parametric distribution family for the lifespan. The typical finding from demography is an instationary behaviour of the life expectancy, and a copula models the resulting weak dependence of lifespan and the age at truncation. Our main example is the Farlie-Gumbel-Morgenststern copula. The test is based on Donsker-class arguments and the functional delta method for empirical processes. The assumptions also allow parametric inference, and proofs slightly simplify due to the compact support of the observations. An algorithm with finitely many operations is given for the computation of the test statistic. Simulations becomes necessary for computing the critical value. With the exponential distribution as an example, and for the application to 55{,}000 German double-truncated enterprise lifespans, the constructed Kolmogorov-Smirnov test rejects clearly an age-homogeneous closure hazard.