Probability and Statistics Theory

A section of Mathematics (ISSN 2227-7390).

Section Information

The section Probability and Statistics Theory of Mathematics publishes original contributions that cover recent advances and reviews in the theory and applications of probability and statistics.   

We welcome papers dealing with all aspects of these disciplines, including  the foundations of probability and statistics theory, probability theory on topological structures, combinatorial probability, stochastic geometry, distribution theory, limit theorems, stochastic processes, stochastic analysis, Markov processes, special processes, information-theoretic topics, decision theory, Bayesian problems, sampling theory, parametric and nonparametric inference, multivariate analysis, regression, sequential methods, inference from stochastic processes, survival analysis, data science, and big data.

Special attention will be given to the theory and application of probability in the modeling of random phenomena in the natural sciences, social sciences, and technology. The section is also dedicated to the dissemination of methodological research and statistical techniques based on mathematical theory, analytical, algorithmic, experimental approaches, and computational methods.

Applications of stochastic models and statistical methods to diverse areas such as biology, medicine, epidemiology, economics, computer science, telecommunications modeling, inventories, reliability, queueing theory, statistical physics, optimization, and operations research are very welcome as well. 

Prof. Dr. Antonio Di Crescenzo

Section Editor-in-Chief

Editorial Board

Special Issues

Following special issues within this section are currently open for submissions:

Papers Published

Back to TopTop