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 ...

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 62, No. 1 (2000), pp. 57-75 (19 pages) Hidden Markov models form an extension of mixture models which provides a ...

In this paper, we consider the consistency and asymptotic normality of the maximum likelihood estimator for a possibly non-stationary hidden Markov model where the hidden state space is a separable ...

Erkyihun S.T., E Zagona, B. Rajagopalan, (2017). “Wavelet and Hidden Markov-Based Stochastic Simulation Methods Comparison on Colorado River Streamflow,” Journal of Hydrologic Engineering 2017, 22(9): ...

C. Bracken, B. Rajagopalan, & E. Zagona (2014). “A Hidden Markov Model Combined with Climate Indices for Multi-decadal Streamflow Simulation,” Water Resources Research, 50, 7836-7846. Abstract: ...

Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation This paper proposes a hidden state Markov model (HMM) that incorporates workers’ unobserved labor market attachment into ...

At its core, a Markov chain is a model for predicting the next event in a sequence based only on its state. It possesses ...

This past semester I added research to my already full schedule of math and engineering classes, as any masochistic student eagerly would. Packed schedule aside, how do you pass up the chance to work ...