標題: 設限資料下分量迴歸模型分析之文獻回顧
Quantile Regression Analysis based on Censored Data A Literature Review
作者: 林欣穎
Lin, Hsin-Ying
王維菁
Wang, Wei-Jing
統計學研究所
關鍵字: 分量迴歸模型;設限;Quantile regression model;Censoring
公開日期: 2010
摘要: 在此論文中,我們回顧分量迴歸模型的重要文獻。首先,我們介紹在沒有變數之完整資料下,估計分量的推論技巧,藉此了解分量的幾何結構和分析上問題的困難處。接著,我們引進變數的影響和討論不同的估計程序,並提供幾何上的解釋意義。最後,我們加入設限的影響並且討論幾種修正的估計方法。我們提供系統化的架構,讓讀者透過推論方法基本的建構原則,對分量迴歸模型有初步的了解。
In the thesis, we review important literature on quantile regression models for survival data. First, we introduce the inference techniques for estimating a quantile based on complete data without covariates. This allows us to see the geometric structure and analytical difficulty of the problem. Then we include the effect of covariates and discuss different estimation procedures. Geometric explanations are also provided. Finally the effect of censoring is incorporated and we discuss several approaches of modification. We aim to provide a systematic framework which allows the readers to understand the quantile regression model from fundamental inference principles.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT079826505
http://hdl.handle.net/11536/47671
顯示於類別:畢業論文


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