BAYESIAN ESTIMATION OF PARAMETERS IN THE EXPONENTIATED GUMBEL DISTRIBUTION

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GHOLAMI GHOLAMHOSSEIN

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Journal Paper

Paper Information

Journal: JOURNAL OF STATISTICAL RESEARCH OF IRAN (JSRI) Year:2017 | Volume:13 | Issue:2 Page(s): 181-195

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Information Journal Paper

Title

BAYESIAN ESTIMATION OF PARAMETERS IN THE EXPONENTIATED GUMBEL DISTRIBUTION

Author(s)

GHOLAMI GHOLAMHOSSEIN | Issue Writer Certificate

Keywords

BAYESIAN INFERENCE

EXPONENTIATED DISTRIBUTIONS

GUMBEL DISTRIBUTION

GIBBS SAMPLER

MONTE CARLO MARKOV CHAIN (MCMC) METHOD

METROPOLIS-HASTINGS ALGORITHM

Abstract

The Exponentiated Gumbel (EG) distribution has been proposed to capture some aspects of the data that the GUMBEL DISTRIBUTION fails to specify. In this paper, we estimate the EG’s parameters in the Bayesian framework. We consider a 2-level hierarchical structure for prior distribution.As the posterior distributions do not admit a closed form, we do an approximated inference by using Gibbs and METROPOLIS-HASTINGS ALGORITHM.

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APA: Copy

GHOLAMI, GHOLAMHOSSEIN. (2017). BAYESIAN ESTIMATION OF PARAMETERS IN THE EXPONENTIATED GUMBEL DISTRIBUTION. JOURNAL OF STATISTICAL RESEARCH OF IRAN (JSRI), 13(2), 181-195. SID. https://sid.ir/paper/690872/en

Vancouver: Copy

GHOLAMI GHOLAMHOSSEIN. BAYESIAN ESTIMATION OF PARAMETERS IN THE EXPONENTIATED GUMBEL DISTRIBUTION. JOURNAL OF STATISTICAL RESEARCH OF IRAN (JSRI)[Internet]. 2017;13(2):181-195. Available from: https://sid.ir/paper/690872/en

IEEE: Copy

GHOLAMHOSSEIN GHOLAMI, “BAYESIAN ESTIMATION OF PARAMETERS IN THE EXPONENTIATED GUMBEL DISTRIBUTION,” JOURNAL OF STATISTICAL RESEARCH OF IRAN (JSRI), vol. 13, no. 2, pp. 181–195, 2017, [Online]. Available: https://sid.ir/paper/690872/en

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