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

• Main Authors: JIUN-HAU WU, 吳俊皓
• Other Authors: Yu-Jau Lin
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/eu3654

碩士 === 中原大學 === 應用數學研究所 === 107 === 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.