The Comparison of Parameter Estimation in Exponential Distribution using Maximum Likelihood Method and Bayesian Method

G. Mada, Cecilia Noviyanti Salsinha, Beatrix Farena Mun
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Abstract

This study aims to compare the parameter estimation process on the exponential distribution using the maximum likelihood method and the Bayesian method on service data at Bank BRI Atambua Branch. The result of processing data on 100 service time data obtained parameter values for the maximum likelihood method = 0,050942 and the Bayesian = 1,0008. By using the Akaike Information Criterion (AIC) feasibility test for these parameters, the AIC value for the maximum likelihood method was 797,4122 and the AIC value for the Bayesian method was 3.931,1002 so it can be concluded that the maximum likelihood method is better used to estimate parameters than Bayesian method.
极大似然法与贝叶斯法在指数分布参数估计中的比较
本研究旨在比较利用极大似然方法和贝叶斯方法对BRI银行Atambua分行业务数据的指数分布参数估计过程。对100个服役时间数据进行处理,得到最大似然法的参数值= 0,050942,贝叶斯法的参数值= 1,0008。通过对这些参数进行赤池信息准则(Akaike Information Criterion, AIC)可行性检验,最大似然方法的AIC值为797,4122,贝叶斯方法的AIC值为3.931,1002,可见最大似然方法比贝叶斯方法更适合用于参数估计。
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