Abstract

A new four parameter extreme value distribution is defined and studied. Various structural properties of the proposed distribution including ordinary and incomplete moments, generating functions, residual and reversed residual life functions, order statistics are investigated. Some useful characterizations based on two truncated moments as well as based on the reverse hazard function and on certain functions of the random variable are presented. The maximum likelihood method is used to estimate the model parameters. Further, we propose a new extended regression model based on the logarithm of the new distribution. The new distribution is applied to model three real data sets to prove empirically its flexibility.

Highlights

  • The theory of extreme value distribution is very popular in statistics and is devoted to study of stochastical series of independent and identically distributed random variables

  • We introduce a new four-parameter extreme value model called the Topp-Leone generated Fréchet (TLGFr) distribution, which extends the Fréchet distribution

  • Characterizations based on two truncated moments as well as based on reverse hazard function and on certain functions of the random variable are presented

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Summary

A NEW DISTRIBUTION FOR EXTREME VALUES

G. Ramires[3,4], G.

Introduction
Quantile function
Moments and cumulants
Moment generating function
Incomplete moments and mean deviations
Residual and reversed residual life functions
Order statistics
Characterizations
Characterizations based on two truncated moments
Characterization in terms of the reverse hazard function
Characterization based on certain functions of the random variable
Parameter estimation
Simulation study
Regression model
Applications
Breaking stress of carbon ftbers
Strength of glass ftbers
Application of log-TLFr regression model
Conclusions

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