Integral part models in information systems and educational processes
Constantinos T. Artikis, Panagiotis T. Artikis · Journal of Discrete Mathematical Sciences and Cryptography · 2009
Integral part models and discrete selfdecomposable random variables, which take values in the set of nonnegative integers, are generally considered as very strong tools of probability theory for the formulation of stochastic models with particularly significant applications in a wide variety of practical disciplines. The present paper is mainly devoted to the study of selfdecomposabillity of some integral part models and the establishment of applications of such models in information systems and educational processes.