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 ...

Monte Carlo methods have become indispensable in simulating light transport due to their flexibility in handling complex phenomena such as scattering, absorption, and emission in heterogeneous media.

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 ...

Pete Rathburn is a copy editor and fact-checker with expertise in economics and personal finance and over twenty years of experience in the classroom. Getty Images / Monty Rakusen Analysts can assess ...

The application of Bayesian methods to large-scale phylogenetics problems is increasingly limited by computational issues, motivating the development of methods that can complement existing Markov ...

Uncertainty and risk are issues that virtually every business analyst must deal with, sooner or later. The consequences of not properly estimating and dealing with risk can be devastating. There’s a ...