具有依赖状态和符咒的联结持续时间模型

IF 1.5 3区 数学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Simon M.S. Lo , Shuolin Shi , Ralf A. Wilke
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引用次数: 0

摘要

引入了依赖状态和咒语的嵌套阿基米德联结模型,并建立了与具有脆弱性的经典生存模型的联系。该模型放宽了经典生存模型的一个重要限制,因为不可观测异质性的分布允许依赖于可观测协变量。它的模块化结构具有实际的优点,不同的组件可以单独指定,可以顺序或单独进行估计。这使得该模型在实证工作中具有通用性和适应性。将相关的行政数据应用于劳动力市场转型,支持了对依赖结构和边际幸存者模型的灵活规范的需要。传统的马尔可夫链模型在实际应用中存在较大的偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A copula duration model with dependent states and spells
A nested Archimedean copula model for dependent states and spells is introduced and the link to a classical survival model with frailties is established. The model relaxes an important restriction of classical survival models as the distributions of unobservable heterogeneities are permitted to depend on the observable covariates. Its modular structure has practical advantages as the different components can be separately specified and estimation can be done sequentially or separately. This makes the model versatile and adaptable in empirical work. An application to labour market transitions with linked administrative data supports the need for a flexible specification of the dependence structure and the model for the marginal survivals. The conventional Markov Chain Model is shown to give sizeably biased results in the application.
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来源期刊
Computational Statistics & Data Analysis
Computational Statistics & Data Analysis 数学-计算机:跨学科应用
CiteScore
3.70
自引率
5.60%
发文量
167
审稿时长
60 days
期刊介绍: Computational Statistics and Data Analysis (CSDA), an Official Publication of the network Computational and Methodological Statistics (CMStatistics) and of the International Association for Statistical Computing (IASC), is an international journal dedicated to the dissemination of methodological research and applications in the areas of computational statistics and data analysis. The journal consists of four refereed sections which are divided into the following subject areas: I) Computational Statistics - Manuscripts dealing with: 1) the explicit impact of computers on statistical methodology (e.g., Bayesian computing, bioinformatics,computer graphics, computer intensive inferential methods, data exploration, data mining, expert systems, heuristics, knowledge based systems, machine learning, neural networks, numerical and optimization methods, parallel computing, statistical databases, statistical systems), and 2) the development, evaluation and validation of statistical software and algorithms. Software and algorithms can be submitted with manuscripts and will be stored together with the online article. II) Statistical Methodology for Data Analysis - Manuscripts dealing with novel and original data analytical strategies and methodologies applied in biostatistics (design and analytic methods for clinical trials, epidemiological studies, statistical genetics, or genetic/environmental interactions), chemometrics, classification, data exploration, density estimation, design of experiments, environmetrics, education, image analysis, marketing, model free data exploration, pattern recognition, psychometrics, statistical physics, image processing, robust procedures. [...] III) Special Applications - [...] IV) Annals of Statistical Data Science [...]
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