Abstract
In this paper, we use the structure of the standard two-sided power distribution to implement a new version of the hyperbolic secant distribution. This new distribution is more flexible than the hyperbolic secant distribution when it comes to interpreting data presenting an abrupt change in values. In the first part of the paper, we show some of its properties, such as the shape behavior of the probability density and hazard rate functions, and the analysis of moment-type measures. Then, the statistical side of the underlying model is explored. We provide the maximum likelihood estimates for the model parameters, as well as an efficient algorithm to calculate them. After this, to demonstrate the potential of the proposed modeling strategy, we present three real data applications. The beta-normal, power-normal, Kuramaswamy-normal and two-sided generalized normal distribution models are considered as competitors. The results are favorable to the proposed model.
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