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Modeling and Estimation of a Bivariate Pareto Distribution using the Principle of Maximum Entropy

Author:

Jagathnath K.M. Krishna

Economics Research Division, CSIR-Central Leather Research Institute, Adyar, Chennai – 600 020,, IN
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Abstract

In this paper we modeled a bivariate Pareto I distribution using the method of principle of maximum entropy probability distribution. Properties of the model are discussed. Further the estimation of the parameters involved in the model is done in two stages using two different methods namely, principle of maximum entropy estimation (POME) and maximum likelihood estimation. From the simulation study conducted to compare the performance of the estimates obtained by the above two methods, we conclude that POME method is performing better than MLE and the two methods are comparable.

DOI: http://dx.doi.org/10.4038/sljastats.v15i3.7795

How to Cite: Krishna, J.K.M., (2014). Modeling and Estimation of a Bivariate Pareto Distribution using the Principle of Maximum Entropy. Sri Lankan Journal of Applied Statistics. 15(3), pp.171–184. DOI: http://doi.org/10.4038/sljastats.v15i3.7795
Published on 15 Dec 2014.
Peer Reviewed

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