On parameter estimation of the standard omega distribution

The standard omega distribution is defined on the unit interval so that it a probabilistic model for observations in rates and percentages. It is, fact, form of exponentiated half logistic distribution. In this work, we first give detailed shape analysis from which observe another flexible beta-like We can be J-shaped, reverse U-shaped, unimodal show left right skewness according to values its parameters. Contrary ordinary beta, has advantage having clear function. then discuss existence uniqueness maximum likelihood estimators Bayesian estimate parameters will great possible practitioners since possibility finding spurious solution equations disappears then. comparison these with existing ones general made help simulation study. Two real data fitting demonstrations prove usefulness among other distributions such as Kumaraswamy, log-Lindley Topp–Leone.