In this article, Burr III distribution is proposed with a significantly improved functional form. This new modification has enhanced the flexibility of classical ability to model all shapes hazard rate function including increasing, decreasing, bathtub, upside-down and nearly constant. Some its elementary properties, such as rth moments, sth incomplete moment generating function, skewness, kurt...

The Burr III distribution properly approximates many familiar distributions such as Normal, Lognormal, Gamma, Weibull, and Exponential distributions. It plays an important role in reliability engineering, statistical quality control, and risk analysis models. The Burr III distribution has four parameters known as location, scale, and two shape parameters. The estimation process of these paramet...

Nowadays every business is using different quantitative measures and techniques to assess peiformance of their products! services. It is well known that different manufacturing processes very often manufacture products with quality characteristics that do not follow normal distribution. In such cases, fitting a known non-normal distribution to these quality characteristics would lead to erroneo...

In this paper, we study the estimation problems for the Burr type III distribution based on a complete sample. The maximum likelihood method is used to derive the point estimators of the parameter. An exact confidence interval and an exact joint confidence region for the parameters are constructed. Two numerical examples with real data set and simulated data, are presented to illustrate the met...

A new family of distributions called exponentiated Kumaraswamy-Dagum (EKD) distribution is proposed and studied. This family includes several well known sub-models, such as Dagum (D), Burr III (BIII), Fisk or Log-logistic (F or LLog), and new sub-models, namely, Kumaraswamy-Dagum (KD), Kumaraswamy-Burr III (KBIII), Kumaraswamy-Fisk or Kumaraswamy-Log-logistic (KF or KLLog), exponentiated Kumara...

In this article, additional properties of the Gumbel-Burr XII distribution, denoted by (GBXII(L)), defined in (Osatohanmwen et al., 2017), are studied. We consider some useful characterizations for GBXII(L) distribution and its properties. A simulation study is conducted to assess performance MLEs usefulness illustrated means three real data sets. The suggests that maximum likelihood method can...

This article addresses the various mathematical and statistical properties of Burr type XII distribution (such as quantiles, moments, moment generating function, hazard rate, conditional mean residual lifetime, past deviation about median, stochasic ordering, stress-strength parameter, entropies, Bonferroni Lorenz curves order statistics) are derived. We discuss some exact expressions recurrenc...