The applications of Normal distribution in literature are verse, the new modified univariate normal power is a which adequate for modelling bimodal data. There many data that would have been modelled by distribution, but because their bimodality, they not, since unimodal. In this paper, extension linear model called normal-Power generalized model, derived from T-Power $$\lbrace$$ Logistic $$\rb...

The log-logistic distribution is widely used in different fields of study such as survival analysis, hydrology, insurance, and economics. Recently, Ahsanullah Alzaatreh studied the best linear unbiased estimators for location scale parameters three-parameter model. same authors also propose a shift-invariant Hill estimator unknown shape parameter. In this work, we new estimation method We deriv...

Along with the widespread application of the electronic commerce in the modern business, the logistic distribution has become increasingly important. More and more enterprises recognize that the logistic distribution plays an important role in the process of production and sales. A good routing for logistic distribution can cut down transport cost and improve efficiency. In order to cut down tr...

We propose a new prior distribution for classical (non-hierarchical) logistic regression models, constructed by first scaling all nonbinary variables to have mean 0 and standard deviation 0.5, and then placing independent Student-t prior distributions on the coefficients. As a default choice, we recommend the Cauchy distribution with center 0 and scale 2.5, which in the simplest setting is a lo...

Log-logistic distribution is a very important reliability model as it fits well in many practical situations of reliability data analyses. Another important feature with the log-logistic distribution lies in its closed form expression for survival and hazard functions that makes it advantageous over log-normal distribution. It is therefore more convenient in handling censored data than the log-...