In light of recent global shocks and rising external volatility, there is a growing need to effectively monitor short-term economic fluctuations, especially in countries with limited access to ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

Our recently developed fully robust Bayesian semiparametric mixed-effect model for high-dimensional longitudinal studies with heterogeneous observations can be implemented through this package. This ...

A Markov model was constructed to compare CMT versus RT alone for patients with early-stage ENKTCL, according to five risk groups defined by NRI model. Transition probabilities, effectiveness, and ...

The amino acid sequence of the transmembrane protein and its corresponding positions on the cell membrane are transformed into a hidden Markov process. After evaluating the parameters, the Viterbi ...

School of Economics, The University of Nottingham-Ningbo, Ningbo, China. The study focuses on identifying and distinguishing whether there are differences between those students receiving special ...

Abstract: We use Markov categories to generalize the basic theory of Markov chains and hidden Markov models to an abstract setting. This comprises characterizations of hidden Markov models in terms of ...

Understanding what causes disease is key to improving its treatment and prevention. Large health studies like UK Biobank measure thousands of possible causes of disease. Traditionally, scientists have ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Concentrations of bioaccumulative contaminants in fish increase with their size and ...

Abstract: Hidden Markov models (HMMs) are a powerful class of dynamical models for representing complex systems that are partially observed through sensory data. Existing data collection methods for ...