The Median Based Unit Weibull is a new 2 parameter unit Weibull distribution defined on the unit interval (0,1). Estimation of the parameters using MLE encountered some problems like large variance. Using generalized method of moments (GMMs) and percentile method may ameliorate this condition. This paper introduces GMMs and the percentile methods for estimating the parameters of the new distribution with illustrative real data analysis.

Parametric quantile regression is illustrated for the one parameter new unit Rayleigh distribution called Median Based Unit Rayleigh distribution (MBUR) distribution. The estimation process using reparameterized maximum likelihood function is highlighted with real dataset example. The inference and goodness of fit is also explored.

A new 2 parameter unit Weibull distribution is defined on the unit interval (0,1). The methodology of deducing its PDF, some of its properties and related functions are discussed. The paper is supplied by many figures illustrating the new distribution and how this can make it illegible to fit a wide range of skewed data. The new distribution holds a name (Attia) as a nickname.

The importance of continuously emerging new distribution is a mandate to understand the world and environment surrounding us. In this paper, the author will discuss a new distribution defined on the interval (0,1) as regards the methodology of deducing its PDF, some of its properties and related functions. A simulation and real data analysis will be highlighted.

Estimation of constant coefficient in simple linear regression analysis Using Likelihood Ratio Test Revealing a Probability Distribution Present in a Complex Plane, raise the question can the probability distribution be present in a complex plane?

In this article , Poisson regression model is used to relates the rates of transition among states to the covariates .

A document by Iman Mohammed Attia Abd-Elkhalik Abo Elreesh . Click on the document to view its contents.

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