Discover how Markov chains predict real systems, from Ulam and von Neumann’s Monte Carlo to PageRank, so you can grasp ...
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 ...
Markov chain models and phase-type distributions have emerged as powerful tools in healthcare analytics, offering a robust framework for understanding and predicting patient trajectories throughout ...
Nonparametric identification and maximum likelihood estimation for finite-state hidden Markov models are investigated. We obtain identification of the parameters as well as the order of the Markov ...
Sparse early-stage data limits accurate geological risk assessment, increasing the chance of undetected hazards ahead of the TBM. By integrating borehole-derived information through an observation ...
Journal of Applied Econometrics, Vol. 20, No. 2, Recent Developments in Business Cycle Analysis (2005), pp. 253-274 (22 pages) The objective of this paper is to evaluate the effectiveness of using a ...
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