Estimasi Parameter Distribusi Mixture Eksponensial dan Weibull dengan Metode Bayesian Markov Chain Monte Carlo

Ulfa Destiarina, Mustika Hadijati, D. Komalasari, Nurul Fitriyani
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Abstract

In parameter estimation, sometimes there are several problems that require the completion of a mixture distribution. This study aimed to apply the parameter estimation of exponential and Weibull mixture distribution in simulation data using the Bayesian Markov Chain Monte Carlo (MCMC) estimation method. The results obtained indicate that the analytic calculations of parameter estimation were more accurate than the calculations with the help of software, based on the terms of the suitability of the theory and its integration process.
以巴耶西安·马尔科夫链的方法计算指数的混频器和维布里尔的配送参数
在参数估计中,有时有几个问题需要完成混合分布。本研究旨在利用贝叶斯马尔可夫链蒙特卡罗(MCMC)估计方法对模拟数据进行指数和威布尔混合分布的参数估计。结果表明,从理论的适用性和理论的整合过程来看,参数估计的解析计算比软件计算更准确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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