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4. ESTIMATION OF THE PARAMETERS FOR POWER FUNCTION DISTRIBUTION BASED ON TYPE-II DOUBLY CENSORED SAMPLE.

Author

Sathyareji, G. S. and Abdul-Sathar, E. I.

Subjects
*POWER distribution networks, *SAMPLING (Process), *BAYES' estimation, *ERROR functions, *MAXIMUM likelihood statistics, *PARAMETER estimation, *ENTROPY, *INTEGRATED squared error, *FORECASTING, *SAMPLE size (Statistics), *APPROXIMATION theory, *COST functions
Abstract

In this paper, we propose the Bayes estimators of unknown parameters of power function distribution in the context of double censoring. The maximum-likelihood estimators (MLEs) for the power function parameters are derived. Bayes estimators are derived using the squared error loss function, entropy loss function, and linex loss function using the Lindley approximation and the importance sampling procedures. We also introduced sample prediction estimates using Bayesian techniques. Finally, we perform a simulation study to compare all the proposed estimation methods and analyze a real-life data set for illustration purposes. [ABSTRACT FROM AUTHOR]

Published
2023

9. Bayesian estimation of Lorenz curve, Gini-index and variance of logarithms in a Pareto distribution

Author

Abdul-Sathar, E. I., Jeevanand, E. S., Muraleedharan Nair, K. R., Abdul-Sathar, E. I., Jeevanand, E. S., and Muraleedharan Nair, K. R.

Abstract

In this article, we estimate Lorenz curve, Gini-index and variance of logarithms for Pareto distribution using Bayesian framework with a conjugate prior. Our proposed Bayesian estimators are compared using a Monte Carlo study, to the MLE estimator proposed by Moothathu (1990) in terms of variance. It is found that the proposed estimators are highly efficient.

Published
2007

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