JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2021, Vol. 56 ›› Issue (7): 46-52.doi: 10.6040/j.issn.1671-9352.0.2020.390

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Bayesian inference of Poisson distribution based on left truncated and right censored data

HU Jiang-shan1, SUI Yun-yun1, FU Yun-peng2   

  1. 1. School of Mathematics and Information Science, Weifang University, Weifang 261061, Shandong, China;
    2. School of Economics, Liaoning University, Shenyang 110036, Liaoning, China
  • Published:2021-07-19

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Abstract: The Bayesian inference of Poisson distribution in left truncated and right censored data is studied. The maximum likelihood estimation method and Bayesian estimation are respectively used to estimate the unknown parameters. Meanwhile the corresponding confidence intervals are given, and stochastic simulations are carried out. It is found that in the case of small sample, the accuracy of Bayesian estimator is higher than that of maximum likelihood estimator, while in the case of large sample, the accuracy of these two estimators is not much different. In terms of confidence interval, the confidence interval of the highest posterior probability density constructed is indeed more effective than the traditional confidence interval, no matter it is a small sample or a large sample.

Key words: Bayesian estimation, prior distribution, confidence interval

CLC Number: 

  • O213
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