In risk analysis based on Bayesian framework, premium calculation requires specification of a prior distribution for the risk parameter in the heterogeneous portfolio. When the prior knowledge is vague, the E-Bayesian and robust Bayesian analysis can be used to handle the uncertainty in specifying the prior distribution by considering a class of priors instead of a single prior. In this paper, we study the E-Bayes and robust Bayes premium estimation and prediction in exponential model under the squared log error loss function. A prequential analysis in a simulation study is carried out to compare the proposed predictors. Finally, a real data example is included for illustrating the results
Kiapour,A. (2022). Bayes, E-Bayes and Robust Bayes Premium Estimation and Prediction under the Squared Log Error Loss Function. Journal of the Iranian Statistical Society, 17(1), 33-47. doi: 10.29252/jirss.17.1.33
MLA
Kiapour,A. . "Bayes, E-Bayes and Robust Bayes Premium Estimation and Prediction under the Squared Log Error Loss Function", Journal of the Iranian Statistical Society, 17, 1, 2022, 33-47. doi: 10.29252/jirss.17.1.33
HARVARD
Kiapour A. (2022). 'Bayes, E-Bayes and Robust Bayes Premium Estimation and Prediction under the Squared Log Error Loss Function', Journal of the Iranian Statistical Society, 17(1), pp. 33-47. doi: 10.29252/jirss.17.1.33
CHICAGO
A. Kiapour, "Bayes, E-Bayes and Robust Bayes Premium Estimation and Prediction under the Squared Log Error Loss Function," Journal of the Iranian Statistical Society, 17 1 (2022): 33-47, doi: 10.29252/jirss.17.1.33
VANCOUVER
Kiapour A. Bayes, E-Bayes and Robust Bayes Premium Estimation and Prediction under the Squared Log Error Loss Function. JIRSS, 2022; 17(1): 33-47. doi: 10.29252/jirss.17.1.33
Journal of the Iranian Statistical Society