English  |  正體中文  |  简体中文  |  Items with full text/Total items : 76531/76531 (100%) Visitors : 29682429      Online Users : 289
 RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
 Scope All of NCUIR 理學院    數學研究所       --博碩士論文 Tips: please add "double quotation mark" for query phrases to get precise resultsplease goto advance search for comprehansive author search Adv. Search
 NCU Institutional Repository > 理學院 > 數學研究所 > 博碩士論文 >  Item 987654321/7943

 Please use this identifier to cite or link to this item: `http://ir.lib.ncu.edu.tw/handle/987654321/7943`

 Title: 數據依賴誤差之階梯函數迴歸的貝氏方法;A Bayesian Approach to Step Function Regression with Data Dependent Error Authors: 陳孜圩;Tzu-yu Chen Contributors: 數學研究所 Keywords: 變點問題;馬可夫鏈蒙地卡羅法;階梯函數;比較型基因體雜交分析技術;貝氏迴歸模型;Markov chain Monte Carlo;change point problem;comparative genomic hybridization;step function;Bayesian regression model Date: 2008-06-06 Issue Date: 2009-09-22 11:09:45 (UTC+8) Publisher: 國立中央大學圖書館 Abstract: 在這篇論文中，我們將 Wen et al. 在2006年提出的貝氏迴歸模型做推廣，考慮其誤差項會受到迴歸函數的函數值所影響。除此之外，我們也更近一步地探討，在每一個位置附近發生跳點的機率以及其所跳的高度之間的關係。 One of the purposes of this thesis is to extend the Bayesian step-function regression model of Wen et al. (2006) to allow for more general noise term so that the error term may vary with the ratio itself, which is also a familiar phenomenon in regression analysis. The other purpose of this thesis is to explore in more detail the relation between the size of the jump at a point of the posterior mode and posterior probability that it is a jump point. Appears in Collections: [數學研究所] 博碩士論文

Files in This Item:

File SizeFormat