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  • 學位論文

貝氏對右設限和現狀數據混合資料下累積風險之研究

Bayesian cumulative hazard rate estimation for mixed right-censored and current status data

指導教授 : 吳裕振

摘要


本論文研究右設限資料和現狀數據之累積風險函數之估計,在王天佑(2015)用貝氏方法對其分佈函數做估計。而本篇論文在同樣資料情況下,與它不同的是估計累積風險函數,而使用方法也是貝氏統計,也是用馬可夫鏈蒙地卡羅法來做計算。而我們選擇直接對累積風險函數做估計,因為它是卡氏模型的特別情況,若考慮共變量,則可採用此方法來估計,其模擬結果符合理論。

並列摘要


The study investigated the estimation of the cumulative hazard function for mixed right-censored and current status data. Tian-yo Wang (2015) used Bayesian approach to estimate their distribution function. The study used Bayesian statistics and Markov chain Monte Carlo method to calculate the similar data, which is different in estimated cumulative hazard function. We chose to directly estimate cumulative hazard function because it was a special case of Cartesian model. Considering the covariate, we will use the method to estimate the data. Its simulation results consistent with theoretical.

參考文獻


[2 ]G. Casella , R.L. Berger ” Statistical inference ” , Duxbury Press 1990.
[3 ]C. P. Robert, G. Casella ” Monte Carlo Statistical Methods
[4 ]P. Green ” Reversible jump Markov chain Monte Carlo computation and
Bayesian model determination ”
[5 ]王天佑 (2015) 右設限與現狀混合資料伯氏─貝氏存活率之分析,初稿

被引用紀錄


林智謙(2015)。右設限和現狀數據混合資料下累積風險之研究〔碩士論文,中原大學〕。華藝線上圖書館。https://doi.org/10.6840/cycu201500152

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