標題: Inference for bivariate survival data by copula models adjusted for the boundary effect
作者: Ding, Aidong Adam
Wang, Weijing
統計學研究所
Institute of Statistics
公開日期: 1-Jan-2007
摘要: Copula models describe the dependence structure of two random variables separately from their marginal distributions and hence are particularly useful in studying the association for bivariate survival data. Semiparametric inference for bivariate survival data based on copula models has been studied for various types of data, including complete data, right-censored data, and current status data. This article discusses the boundary effect on these inference procedures, a problem that has been neglected in the previous literature. Specifically, asymptotic distribution of the association estimator on the boundary of parameter space is derived for one-dimensional copula models. The boundary properties are applied to test independence and to study the estimation efficiency. Simulation study is conducted for the bivariate right-censored data and current status data.
URI: http://dx.doi.org/10.1080/03610920701386901
http://hdl.handle.net/11536/11392
ISSN: 0361-0926
DOI: 10.1080/03610920701386901
期刊: COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Volume: 36
Issue: 13-16
起始頁: 2927
結束頁: 2936
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