A New Technique to Generate Families of Continuous Distributions

We introduce a novel technique for producing several families of distri-
butions: the alpha-log-power transformed method. The novelty of our new
approach lies in the fact that it adds one new shape parameter and was
not derived from any established parent model. Some examples of the new
family are presented. Also, some important statistical properties of the new
family are studied. The maximum likelihood estimation approach is utilized
to estimate the model parameters of the new family. To evaluate the perfor-
mance of the estimators, Monte Carlo simulation is conducted using some
arbitrary baseline distributions namely the Weibull, Burr-XII and Pareto
distribution. Two real datasets are used to empirically show the potential
signicance and applicability of the alpha log power transformed Weibull.
The alpha log power transformed Weibull is a very competitive model for
characterizing observations in survival analysis.