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We develop two novel approaches for constructing skewed and bimodal flexibledistributions that can effectively generalize classical symmetricdistributions. We illustrate the application of introduced techniques byextending normal, student-t, and Laplace distributions. We also study theproperties of the newly constructed distributions. The method of maximumlikelihood is proposed for estimating the model parameters. Furthermore, theapplication of new distributions is represented using real-life data.

Developing flexible classes of distributions to account for both skewness and bimodality