Dados do Trabalho

Título

EFFICIENT CLOSED-FORM MAXIMUM A POSTERIORI ESTIMATORS FOR THE GAMMA DISTRIBUTION

Resumo

We proposed a new class of maximum a posteriori estimators for the parameters of the Gamma distribution. These estimators have simple closed-form expressions and can be rewritten as a bias-corrected maximum likelihood estimators presented by Ye and Chen (2017). A simulation study was carried out to compare different estimation procedures. Numerical results reveal that our new estimation scheme outperforms the existing closed-form estimators and produces extremely efficient estimates for both parameters, even for small sample sizes.

Palavras-chave

Gamma distribution; Bayesian Analysis; Maximum likelihood estimators; Closed-Form estimator.