Discover how Markov chains predict real systems, from Ulam and von Neumann’s Monte Carlo to PageRank, so you can grasp ...

Markov Chain Monte Carlo (MCMC) methods have become indispensable in contemporary statistical science, enabling researchers to approximate complex probability distributions that are otherwise ...

Marquette University has named Marko Bastl as its next director of its Center for Supply Chain Management. Bastl has been an associate professor of supply chain management with Marquette since August ...

Software engineer Sai Bhargav Yalamanchi notes that mathematical tools helping practitioners interpret uncertainty have ...

We consider the recently introduced Transformation-based Markov Chain Monte Carlo (TMCMC) (Stat. Methodol. 16 (2014) 100–116), a methodology that is designed to update all the parameters ...

Markov chains provide a fundamental framework for modelling stochastic processes, where the next state depends solely on the current state. Hidden Markov models (HMMs) extend this framework by ...

We describe the ergodic properties of some Metropolis–Hastings algorithms for heavy-tailed target distributions. The results of these algorithms are usually analyzed under a subgeometric ergodic ...

Amid all the hype about AI it sometimes seems as though the world has lost sight of the fact that software such as ChatGPT contains no intelligence. Instead it’s an extremely sophisticated system for ...