Bayesian estimation of the number of species from Poisson-Lindley stochastic abundance model using non-informative priors
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Date
2024
Authors
Journal Title
Computational Statistics
Journal ISSN
Volume Title
Publisher
Springer Science and Business Media Deutschland GmbH
Abstract
In this article, we propose a Poisson-Lindley distribution as a stochastic abundance model in which the sample is according to the independent Poisson process. Jeffery�s and Bernardo�s reference priors have been obtaining and proposed the Bayes estimators of the number of species for this model. The proposed Bayes estimators have been compared with the corresponding profile and conditional maximum likelihood estimators for their square root of the risks under squared error loss function (SELF). Jeffery�s and Bernardo�s reference priors have been considered and compared with the Bayesian approach based on biological data. � The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
Description
Keywords
Abundance species estimation, Bayesian method, Bernardo�s reference prior, Jeffrey�s prior