首页   按字顺浏览 期刊浏览 卷期浏览 Nonparametric Methods for Doubly Truncated Data
Nonparametric Methods for Doubly Truncated Data

 

作者: Bradley Efron,   Vahe Petrosian,  

 

期刊: Journal of the American Statistical Association  (Taylor Available online 1999)
卷期: Volume 94, issue 447  

页码: 824-834

 

ISSN:0162-1459

 

年代: 1999

 

DOI:10.1080/01621459.1999.10474187

 

出版商: Taylor & Francis Group

 

关键词: Bootstrap;Hypothesis test;Luminosity evolution;Lynden-Bell estimator;Markov chain Monte Carlo;Quasars;Self-consistency;Tau test

 

数据来源: Taylor

 

摘要:

Truncated data play an important role in the statistical analysis of astronomical observations as well as in survival analysis. The motivating example for this article concerns a set of measurements on quasars in which there is double truncation. That is, the quasars are observed only if their luminosity occurs within a certain finite interval, bounded at both ends, with the interval varying for different observations. Nonparametric methods for the testing and estimation of doubly truncated data are developed. These methods extend some known techniques for data that are truncated only on one side, in particular Lynden-Bell's estimator and the truncated version of Kendall's tau statistic. However the kind of hazard function arguments that underlie the one-sided methods fail for two-sided truncation. Bootstrap and Markov Chain Monte Carlo techniques are used here in their place. Finally, we apply these techniques to the quasar data, answering a question about their long-term luminosity evolution.

 

点击下载:  PDF (892KB)



返 回