This paper is devoted to study a form of lognormal distributions family and introduce some of its basic properties. It presents new derivate models that find many applications will be useful for practitioners in various fields. The abstract explores some of the basic characteristics of the family of abnormal distributions and provides some practical methods for analyzing some different applied fields related to theoretical and applied statistical sciences. The proposed model allows for the improvement of the relevance of near-real data and opens broad horizons for the study of phenomena that can be addressed through the results obtained. This study is devoted to a review of fitting data, discuss distribution laws for models and describe the approaches used for parameterization and classification of models. Finally, a set of concluding observations has been developed to track the mix distributions and their adaptation mechanisms.
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