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Abstract
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We study a new family of continuous distributions with two extra shape
parameters called the Burr generalized family of distributions. We investigate
the shapes of the density and hazard rate function. We derive explicit
expressions for some of its mathematical quantities. The estimation of the
model parameters is performed by maximum likelihood. We prove the flexibility
of the new family by means of applications to two real data sets.
Furthermore, we propose a new extended regression model based on the
logarithm of the Burr generalized distribution. This model can be very useful
to the analysis of real data and provide more realistic fits than other special
regression models.
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