The survival function estimation of current status data with dependent censoring
碩士 === 國立中正大學 === 數學系統計科學研究所 === 102 === This thesis focuses on the estimation of the survival function of the failure time under the current status data. Because the failure time may be correlated with the observation time in the practice, we would like to investigate the estimation of the survival...
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ndltd-TW-102CCU004770032019-05-15T21:22:28Z http://ndltd.ncl.edu.tw/handle/zq8bd6 The survival function estimation of current status data with dependent censoring 相關設限下現狀資料存活函數之估計 Yung-Yu Chen 陳永諭 碩士 國立中正大學 數學系統計科學研究所 102 This thesis focuses on the estimation of the survival function of the failure time under the current status data. Because the failure time may be correlated with the observation time in the practice, we would like to investigate the estimation of the survival function of the failure time under dependent censoring. We use the Archimedean Copula model to specify the dependency between the failure time and the observation time. Under the Archimedean Copula model assumption, we adopt a redistribution algorithm to estimate the survival function of the failure time. We examine the finite-sample performance of the proposed approach by simulation studies and compared it with a pool-adjacent-violators type algorithm (Titman, 2013). We also apply our proposed methodology to analyze a practical tumorigenicity data. Jin-Jian Hsieh 謝進見 2014 學位論文 ; thesis 48 en_US |
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碩士 === 國立中正大學 === 數學系統計科學研究所 === 102 === This thesis focuses on the estimation of the survival function of the failure time under the current status data. Because the failure time may be correlated with the observation time in the practice, we would like to investigate the estimation of the survival function of the failure time under dependent censoring. We use the Archimedean Copula model to specify the dependency between the failure time and the observation time. Under the Archimedean Copula model assumption, we adopt a redistribution algorithm to estimate the survival function of the failure time. We examine the finite-sample performance of the proposed approach by simulation studies and compared it with a pool-adjacent-violators type algorithm (Titman, 2013). We also apply our proposed methodology to analyze a practical tumorigenicity data.
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author2 |
Jin-Jian Hsieh |
author_facet |
Jin-Jian Hsieh Yung-Yu Chen 陳永諭 |
author |
Yung-Yu Chen 陳永諭 |
spellingShingle |
Yung-Yu Chen 陳永諭 The survival function estimation of current status data with dependent censoring |
author_sort |
Yung-Yu Chen |
title |
The survival function estimation of current status data with dependent censoring |
title_short |
The survival function estimation of current status data with dependent censoring |
title_full |
The survival function estimation of current status data with dependent censoring |
title_fullStr |
The survival function estimation of current status data with dependent censoring |
title_full_unstemmed |
The survival function estimation of current status data with dependent censoring |
title_sort |
survival function estimation of current status data with dependent censoring |
publishDate |
2014 |
url |
http://ndltd.ncl.edu.tw/handle/zq8bd6 |
work_keys_str_mv |
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