Acta mathematica scientia,Series A ›› 2022, Vol. 42 ›› Issue (6): 1790-1801.

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E-Bayesian Estimation and E-MSE of Failure Probability and Its Applications

Ming Han()   

  1. School of Science, Ningbo University of Technology, Zhejiang Ningbo 315211
  • Received:2021-12-03 Online:2022-12-26 Published:2022-12-16
  • Supported by:
    the NSF of Ningbo Municipality(2019A610041)


In order to measure the estimated error, this paper based on the E-Bayesian estimation (expected Bayesian estimation) introduced the definition of E-MSE (expected mean square error), and derive the expressions of E-Bayesian estimation of failure probability and their the E-MSE under different loss functions (including: squared error loss function and LINEX loss function). By Monte Carlo simulations compared with the performances of the proposed the estimation method (the comparison of the results is based on the E-MSE). Finally, combined with the engine reliability problem, used respectively E-Bayesian estimation method and the MCMC method the calculation and analysis are performed. When considering evaluating the E-Bayesian estimations under different loss functions, this paper proposed the E-posterior risk as an evaluation standard.

Key words: E-Bayesian estimation, E-MSE, Failure probability, Monte Carlo simulation, MCMC method

CLC Number: 

  • O213.2