Data envelopment analysis (DEA) is a mathematical method to evaluate the performance of decision-making units (DMU). In the performance evaluation of an organization based on the classical theory of DEA, input and output data are assumed to be deterministic, while in the real world, the observed values of the inputs and outputs data are mainly fuzzy and random. A normal distribution is a contin...

‎Here we consider  a new class of skew logistic  distribution as a generalized mixture of the standard logistic and skew logistic distributions‎, ‎and study some of its important aspects‎. ‎The tail behaviour of the  distribution is compared with that of the skew logistic distribution and a location-scale extension of the distribution is proposed‎. ‎Fu...

Normal state-space models are prevalent, but to increase the applicability of the Kalman filter, we propose mixtures of skewed, and extended skewed, Kalman filters. To do so, the closed skew-normal distribution is extended to a scalemixture class of closed skew-normal distributions. Some basic properties are derived and a class of closed skew-t distributions is obtained. Our suggested family of...

Several papers on distributions to model rates and proportions have been recently published; their fitting in numerous instances is better than the alternative beta distribution, which has distribution follow when it necessary quantify average of a response variable based set covariates. Despite great usefulness this fit responses (0,1) unit interval, its relevance loses objectivity interest qu...

In this article, we establish properties that relate quantiles of the log-skew-normal distribution to its parameters, allowing us investigate relationship between a positive skewed response variable and set explanatory variables via linear regression model. We compute maximum likelihood estimates parameters through correspondence skew-normal models. Monte Carlo simulations show satisfactory per...