逐步型二設限韋伯分配資料之貝氏分析

Bayesian Analysis of Progressive Type II Scheme Data from Weibull Distribution Using R NIMBLE package

吳俊皓(JIUN-HAU WU)

指導教授 ： 林余昭

中原大學/理學院/應用數學研究所/碩士(2019年)

https://doi.org/10.6840/cycu201900347

摘要

貝氏統計現今已廣泛運用在工業、金融、醫學等領域，以往受限於計算較為複雜，但隨著科技的進步，許多統計軟體的出現，使得統計學者在模擬分析上可以省去繁瑣的計算。貝氏方法利用過去的經驗，再結合蒐集的資訊進行分析與模擬。
本研究中，為了討論韋伯分配設限資料之貝氏分析，我們使用R 軟體的NIMBLE套件來對模型參數進行分析研究，利用NIMBLE 套件可以有效且快速的執行馬可夫鏈蒙地卡羅法(MCMC) 來估計模型的參數，對參數進行疊代運算後，觀察參數的估計值是否逼近參數的真實值。

關鍵字

貝氏統計 ； 設限資料 ； 韋伯分配 ； 馬可夫鏈蒙地卡羅法 ； NIMBLE 套件 ； R 軟體

並列摘要

Bayesian statistics have been widely used in industry, finance, medicine and other fields. In the past, it was limited by computational complexity. However, with the advancement of technology, the emergence of many statistical software has enabled statisticians to save cumbersome calculations in simulation analysis. The Bayesian methoduses past experience and combines the collected information for analysis and simulation.
In this article, in order to discuss the Bayesian analysis of Weibull Distribution scheme data, we use the NIMBLE of R package to analyze the model parameters, and the NIMBLE can effectively and quickly perform the Markov Chain Monte Carlo method (MCMC). To estimate the parameters of the model, after the iterative operation of the parameters, observe whether the estimated value of the parameter approximates the true value of the parameter.

並列關鍵字

Bayesian statistics ； scheme data ； Weibull Distribution ； MCMC ； NIMBLE ； R package

參考文獻

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