This study focuses on estimating the reliability of a multicomponent stress-strength model using two Bayesian approaches: E-Bayesian and hierarchical Bayesian. This model follows Inverse Rayleigh distributions with distinct parameters. Additionally, the efficiency of the proposed methods is compared by employing Monte Carlo simulation and analyzing a data set.
Makhdoom, I., Shahrastani, S., & Pak, A. (2023). E-Bayesian and hierarchical Bayesian estimation of reliability in multicomponent stress-strength model based on inverse Rayleigh distribution. Journal of Statistical Modelling: Theory and Applications, 4(1), 95-106. doi: 10.22034/jsmta.2023.3360
MLA
Iman Makhdoom; Shahram Yaghoobzadeh Shahrastani; Abbas Pak. "E-Bayesian and hierarchical Bayesian estimation of reliability in multicomponent stress-strength model based on inverse Rayleigh distribution". Journal of Statistical Modelling: Theory and Applications, 4, 1, 2023, 95-106. doi: 10.22034/jsmta.2023.3360
HARVARD
Makhdoom, I., Shahrastani, S., Pak, A. (2023). 'E-Bayesian and hierarchical Bayesian estimation of reliability in multicomponent stress-strength model based on inverse Rayleigh distribution', Journal of Statistical Modelling: Theory and Applications, 4(1), pp. 95-106. doi: 10.22034/jsmta.2023.3360
VANCOUVER
Makhdoom, I., Shahrastani, S., Pak, A. E-Bayesian and hierarchical Bayesian estimation of reliability in multicomponent stress-strength model based on inverse Rayleigh distribution. Journal of Statistical Modelling: Theory and Applications, 2023; 4(1): 95-106. doi: 10.22034/jsmta.2023.3360
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