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Bayesian Inference on the Generalized Gamma Distribution based on the Characteristic Prior

Article scientifique 2023 Anglais

Résumé

Abstract In this paper, Bayesian inference has been applied to the generalized gamma distribution parameters based on the characteristic prior by utilizing the Fourier transformation of the cumulative distribution function. For comparing the characteristic prior with the informative gamma prior, the mean squared errors and the mean percentage errors for the parameters are studied based on both priors based on symmetric and asymmetric loss functions, via Monte Carlo simulations. The simulation results indicated that characteristic prior, which do not contain hyperparameters, are more efficient than informative gamma prior and provide better estimates. Finally, a numerical example is given to demonstrate the efficiency of the two priors.

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Maswadah, M. (2023). Bayesian Inference on the Generalized Gamma Distribution based on the Characteristic Prior. https://doi.org/10.21203/rs.3.rs-3278597/v1

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Auteur(s)

M. Maswadah

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