Bayesian estimation of the number of species from Poisson-Lindley stochastic abundance model using non-informative priors

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dc.contributor.authorPathak A.
dc.contributor.authorKumar M.
dc.contributor.authorSingh S.K.
dc.contributor.authorSingh U.
dc.contributor.authorKumar S.
dc.date.accessioned2025-01-13T07:03:05Z
dc.date.available2025-01-13T07:03:05Z
dc.date.issued2024
dc.description.abstractIn 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.
dc.identifier.doi10.1007/s00180-024-01464-7
dc.identifier.issn9434062
dc.identifier.urihttps://dl.bhu.ac.in/ir/handle/123456789/957
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.subjectAbundance species estimation
dc.subjectBayesian method
dc.subjectBernardo�s reference prior
dc.subjectJeffrey�s prior
dc.titleBayesian estimation of the number of species from Poisson-Lindley stochastic abundance model using non-informative priors
dc.typeArticle
journal.titleComputational Statistics
journalvolume.identifier.volume39

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