Generalized hyperbolic secant distribution: Properties, estimation, and applications

In this study, we define a generalized hyperbolic secant distribution. Poor fit to heavy tailed data sets is repeatedly obtained by existing three-parameter distributions. Only three parameters are considered in the proposed new distribution and it fits left- right-tailed better than various We study some properties of distribution, namely, mode, skewness, kurtosis, hazard function, moments, mean deviation, Shannon entropy. Seven different frequentist methods for estimating briefly described. A simulation also conducted compare performances estimation. The usefulness model demonstrated applying two real-life data.