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Markov Chain Monte Carlo (MCMC)
Resonance - Journal of Science Education, 2022Vivek S Borkar, Borkar Vivek S
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Chemistry - an Asian Journal, 2018
AbstractA CoII coordination polymer built from a mixed azide and zwitterionic pyridinium ions and its temperature‐dependent magnetic properties are described. We used the Markov chain Monte Carlo (MCMC) method to fit the data, and found the following results: (1) there are strong correlations between the model parameters; (2) the data at above 28 K are
Zhe Xue, Qi-Hua Zhao
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AbstractA CoII coordination polymer built from a mixed azide and zwitterionic pyridinium ions and its temperature‐dependent magnetic properties are described. We used the Markov chain Monte Carlo (MCMC) method to fit the data, and found the following results: (1) there are strong correlations between the model parameters; (2) the data at above 28 K are
Zhe Xue, Qi-Hua Zhao
exaly +3 more sources
Health Information Science and Systems, 2021
Vital signal renovation plays an important role in a wide range of applications, including signal analysis and diagnosing diseases through it. Therefore, it is salient to get the main content of the vital signal. In this research, a new approach to the problem of noise removal from vital signals is presented based on random optimization through Monte ...
Kianoush Fathi Vajargah +2 more
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Vital signal renovation plays an important role in a wide range of applications, including signal analysis and diagnosing diseases through it. Therefore, it is salient to get the main content of the vital signal. In this research, a new approach to the problem of noise removal from vital signals is presented based on random optimization through Monte ...
Kianoush Fathi Vajargah +2 more
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Sequential Markov Chain Monte Carlo (MCMC) model discrimination
The Canadian Journal of Chemical Engineering, 2012AbstractIn this paper a new approach to model discrimination is presented that takes advantage of Markov Chain Monte Carlo (MCMC) methods. It combines an experimental criterion first proposed by Roth (Roth, Design of Experiments for Discrimination Among rival Models, PhD, Thesis, Princeton University, New Jersey, USA, 1965) with an adaptation of a ...
Samira Masoumi +2 more
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The Usage of Markov Chain Monte Carlo (MCMC) Methods in Time-varying Volatility Models
Journal of Risk & Control, 2023Abstract Markov Chain Monte Carlo (MCMC) techniques, in the context of Bayesian inference, constitute a practical and effective tool to produce samples from an arbitrary distribution. These algorithms are applied to calculate parameter values of predictive models of the phenomenon of varying volatility in data time series.
Emmanouil Garefalakis +2 more
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Markov chain Monte Carlo (MCMC) method for parameter estimation of nonlinear dynamical systems
2015 IEEE International Conference on Signal and Image Processing Applications (ICSIPA), 2015This manuscript is concerned with parameter estimation of nonlinear dynamical system. Bayesian framework is very useful for parameter estimation, Metropolis-Hastings (MH) algorithm is proposed for constructing the posterior density, which is main working procedure of Bayesian analysis.
Muhammad Javvad ur Rehman +2 more
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A primer for data assimilation with ecological models using Markov Chain Monte Carlo (MCMC)
Oecologia, 2011Data assimilation, or the fusion of a mathematical model with ecological data, is rapidly expanding knowledge of ecological systems across multiple spatial and temporal scales. As the amount of ecological data available to a broader audience increases, quantitative proficiency with data assimilation tools and techniques will be an essential skill for ...
Zobitz, J. M. +3 more
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An example of complex modelling in dentistry using Markov chain Monte Carlo (MCMC) simulation.
Community dental health, 2002In the usual regression setting one regression line is computed for a whole data set. In a more complex situation, each person may be observed for example at several points in time and thus a regression line might be calculated for each person.
Helfenstein, Ulrich +3 more
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A Distributed Computer System for Parallel Markov Chain Monte Carlo (MCMC)
Inquiry@Queen's Undergraduate Research Conference Proceedings, 2018A ubiquitous problem in physics is to determine expectation values of observables associated with a system. This problem is typically formulated as an integration of some likelihood over a multidimensional parameter space. In Bayesian analysis, numerical Markov Chain Monte Carlo (MCMC) algorithms are employed to solve such integrals using a fixed ...
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Markov Chain Monte Carlo (MCMC) methods for parameter estimation of a novel hybrid redundant robot
Fusion Engineering and Design, 2011Abstract This paper presents a statistical method for the calibration of a redundantly actuated hybrid serial-parallel robot IWR (Intersector Welding Robot). The robot under study will be used to carry out welding, machining, and remote handing for the assembly of vacuum vessel of International Thermonuclear Experimental Reactor (ITER). The robot has
Yongbo Wang, Huapeng Wu, Heikki Handroos
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