Monte Carlo methods and Markov Chain algorithms have long been central to computational science, forming the backbone of numerical simulation in a variety of disciplines. These techniques employ ...

We extend the definition of level-crossing ordering of stochastic processes, proposed by Irle and Gani (2001), to the case in which the times to exceed levels are compared using an arbitrary ...

Models suitable for statistical inference in Markov chains are considered featuring various forms of stochastic entry, including Poisson, renewable binomial pool, uncertain pool size, negative ...

Random walks serve as fundamental models in the study of stochastic processes, simulating phenomena ranging from molecular diffusion to queuing networks and financial systems. Their inherent ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I closely examine an innovative way of ...