Modeling and Estimation of a Bivariate Pareto Distribution using the Principle of Maximum Entropy
IR@CLRI: CSIR-Central Leather Research Institute, Chennai
View Archive Info| Field | Value | |
| Title |
Modeling and Estimation of a Bivariate Pareto
Distribution using the Principle of Maximum Entropy
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| Creator |
K.M, Jagathnath Krishna
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| Subject |
Technology Management
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| Description |
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.
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| Publisher |
The Institute of Applied Statistics, Sri Lanka
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| Date |
2014-12-15
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| Type |
Article
PeerReviewed |
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| Format |
application/pdf
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| Identifier |
http://clri.csircentral.net/49/1/CSIR-CLRI%20Communication%20No.%201028%20%28Full%20Text%29.pdf
K.M, Jagathnath Krishna (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. ISSN ISBN-1391-4987 |
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| Relation |
http://http://sljastats.sljol.info/articles/abstract/10.4038/sljastats.v15i3.7795/
http://clri.csircentral.net/49/ |
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