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Article type: Research Article
Authors: Mahajan, Kalpana K. | Arora, Sangeeta; * | Kaur, Kamaljit
Affiliations: Department of Statistics, Panjab University, Chandigarh, India
Correspondence: [*] Corresponding author: Sangeeta Arora, Department of Statistics, Panjab University, Chandigarh-160014, India, Tel.: +91 0172 2541776 (office), +91 9876366604; E-mail: [email protected].
Abstract: Bayes estimators are obtained in case of Pareto distribution for its shape parameter, mean income, Gini index and a Poverty measure for both censored and complete setup. The said estimators are obtained using Jeffreys' non-informative invariant prior and the extension of Jeffreys' prior information. Using simulation techniques, the relative efficiency of proposed estimators with the existing estimators using two-parameter exponential prior is obtained. It turns out that the Bayesian method with Jeffreys' non-informative invariant prior results in smaller expected loss function as compared to existing estimators using two-parameter exponential prior.
Keywords: Gini index, poverty measure, bayes estimator, pareto distribution, non-informative prior, squared error loss function (SELF)
DOI: 10.3233/MAS-140312
Journal: Model Assisted Statistics and Applications, vol. 10, no. 1, pp. 63-72, 2015
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