We propose an extension of Hidden Markov Model (HMM) to support second-order Markov dependence in the observable random process. We propose a Bayesian method to estimate the parameters of the model ...

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 ...

Statistical models called hidden Markov models are a recurring theme in computational biology. What are hidden Markov models, and why are they so useful for so many different problems?

Drought is a naturally occurring climate phenomenon that significantly affects human and environmental activity, and can be considered one of the most widespread and destructive natural disasters.

Definition A Hidden Markov Model (HMM) is a statistical model that assumes there are underlying, unobservable (hidden) states that drive observable outcomes.

Abstract Wavelet and hidden Markov-based modeling frameworks were developed to better capture the nonstationarity and non-Gaussian characteristics of streamflow that linear models cannot.

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 ...

“A Hidden Markov Model Combined with Climate Indices for Multi-decadal Streamflow Simulation,” Water Resources Research, 50, 7836-7846. Abstract: Hydroclimate time series often exhibit very low ...

In a study published in Frontiers of Engineering Management, researchers from Huazhong University of Science and Technology present an online hidden Markov model (OHMM) for predicting geological ...