Applying BBPSO Algorithm to Estimate the Weibull Parameters for Interval Data
碩士 === 國立臺灣科技大學 === 工業管理系 === 100 === In survival analysis, the inspection costs should be concerned. An interval data is widely used in lifetime data analysis. In this article, we present maximum likelihood estimation via Bare Bones Particle Swarm Optimization (BBPSO) algorithm to estimate two para...
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| Format: | Others |
| Language: | zh-TW |
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2012
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| Online Access: | http://ndltd.ncl.edu.tw/handle/63848771088336646450 |
| Summary: | 碩士 === 國立臺灣科技大學 === 工業管理系 === 100 === In survival analysis, the inspection costs should be concerned. An interval data is widely used in lifetime data analysis. In this article, we present maximum likelihood estimation via Bare Bones Particle Swarm Optimization (BBPSO) algorithm to estimate two parameters of Weibull distribution under interval censored data. This approach can produce more accuracy of the parameter estimation for the Weibull distribution. Additionally, the confidence intervals for the estimators are obtained. Compare to the mid-point method and the EM algorithm, it shows that the maximum likelihood estimates based on BBPSO algorithm perform better.
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