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Transmuted Exponentiated Fr ˆechet Distribution: Properties and Applications |
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PP: 379-394 |
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Author(s) |
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I. ELBATAL,
G. ASHA,
VINCENT RAJA,
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Abstract |
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| Transmuted probability distribution corresponding to a distribution function G(x) is defined as
F(x) = (1+l )G(x) −lG(x)2; |l | ≤ 1. In this paper we study some general properties of the transmuted probability distribution
function in relation to the base distribution G(x). In particular the transmuted exponentiated Frˆechet (TEF) distribution is studied in
detail. The different methods of estimation of parameters such as, weighted least squares and the maximum likelihood estimates of
this distribution are studied. Finally, a real time data analysis is performed for this distribution and it is found that this class is more
flexible class and it shown that the TEF distribution is much better fit for data’s originally fitted and analysed using Frˆechet or
Exponentiated Frˆechet distribution. |
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