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Bayesian estimators are obtained in case of Pareto distribution for its shape parameter, mean income, Gini index and a Poverty measure in case of different priors and loss functions for both censored and complete setup. Using simulation techniques, the relative efficiency of proposed estimators is obtained. The robustness of the hyperparameters using (min/max) approach is also carried out for different combinations of hyperparameters.

Produktbeschreibung
Bayesian estimators are obtained in case of Pareto distribution for its shape parameter, mean income, Gini index and a Poverty measure in case of different priors and loss functions for both censored and complete setup. Using simulation techniques, the relative efficiency of proposed estimators is obtained. The robustness of the hyperparameters using (min/max) approach is also carried out for different combinations of hyperparameters.
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Autorenporträt
1. Dr. SANGEETA ARORA, Professor, Department of Statistics, Panjab University, Chandigarh- India. 2. Dr. Kalpana K. Mahajan, Professor, Department of Statistics, Panjab University, Chandigarh- India. 3. Dr. Kamaljit Kaur, Asst. Professor, SGGS College, Chandigarh- India.