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

High-order Markov chain models extend the conventional framework by incorporating dependencies that span several previous states rather than solely the immediate past. This extension allows for a ...

In this paper we show that any separable stochastic process on a compact metric space can be derived from a temporally homogeneous Markov process on the extreme points of a compact convex set of ...

This paper proposes a hidden state Markov model (HMM) that incorporates workers’ unobserved labor market attachment into the analysis of labor market dynamics. Unlike previous literature, which ...