University of Bahrain
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Comparative Study on Estimation of Poisson Parameter in Decision Theoretic Approach

Show simple item record Devi, R. Renuka Subbiah, M. Srinivasan, M.R. 2018-08-01T05:36:15Z 2018-08-01T05:36:15Z 2017-11
dc.identifier.issn 2384-4795
dc.description.abstract It has become imperative in statistical inference to seek beyond the widely practiced squared loss function to accommodate the asymmetric conditions. An attempt in this direction is generally model-specific and the present work has considered inference on count data, as one such model of importance. In particular, the objective is to study the performance of Bayesian estimators for Poisson parameter based on four well established loss functions. The explicit forms are derived and a comprehensive data analyses has been carried out through a simulation study. The study highlights the distinct behaviour of each of the methods to make an appropriate choice based on the small sample behaviour of the data sets. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-ShareAlike 4.0 International *
dc.rights.uri *
dc.subject Poisson mean
dc.subject Loss function
dc.subject Gamma distribution
dc.subject Normal approximation
dc.title Comparative Study on Estimation of Poisson Parameter in Decision Theoretic Approach en_US
dc.type Article en_US
dc.volume 04
dc.issue 02
dc.pagestart 109
dc.pageend 115
dc.source.title International Journal of Computational and Theoretical Statistics
dc.abbreviatedsourcetitle IJCTS

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