The statistics literature is filled with hundreds of continuous multivariate and univariate distributions. Most of the commonly used distributions in reliability, life testing, econometrics, meteorology, actuarial science, and other subject areas are related to other distributions either as special cases, extensions, or limiting distributions. New continuous probabilistic distributions can be very versatile and a variety of uncertainties can be usefully modeled by them. They are of both practical and theoretical interest to scientists in all fields.

The properties of these distributions can include ordinary and incomplete moments, mean deviations, stochastic orderings, order statistics, income measures, entropies, characteristic functions, characterizations, generalizations and related distributions, reliability, transformations, graphical estimation, maximum likelihood estimation, Bayes estimation, other estimation, discrimination, goodness of fit tests, regression models, applications in several areas, multivariate generalizations, and computer software. Despite many recent advances in probabilistic models and methods for the analysis of real data, numerous challenges still remain.

We invite investigators to submit original research articles as well as review articles that propose new probabilistic and statistical models including the study of their mathematical properties. Potential topics include, but are not limited to:

• Compounding distributions, discriminating and fitting models
• Concomitant of order statistics
• Copula theory
• Exponentiated distributions
• Extreme value theory
• Generalized distributions
• Reliability
• Skew models
• Statistical size
• Distributions and survival models

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/jps/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following timetable: