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 ...

Quantum Markov chains (QMCs) represent a natural quantum extension of classical Markov processes, encapsulating memoryless dynamics within quantum systems. They offer a powerful framework to model non ...

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 ...

The Markov Chain Monte Carlo method is arguably the most powerful algorithmic tool available for approximate counting problems. Most known algorithms for such problems follow the paradigm of defining ...

What Is Markov Chain Monte Carlo? Markov Chain Monte Carlo (MCMC) is a powerful technique used in statistics and various scientific fields to sample from complex probability distributions. It is ...

ABSTRACT: An algorithm is being developed to conduct a computational experiment to study the dynamics of random processes in an asymmetric Markov chain with eight discrete states and continuous time.

Let W(π) be either the number of descents or inversions of a permutation $\pi \in S_{n}$. Stein's method is applied to show that W satisfies a central limit theorem ...