Results 41 to 50 of about 1,765,864 (313)
Markov Chain Ontology Analysis (MCOA)
BMC Bioinformatics, 2012 Background Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research.
Frost H, McCray Alexa T
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The Annals of Probability, 1975 We propose a control problem in which we minimize the expected hitting time of a fixed state in an arbitrary Markov chains with countable state space. A Markovian optimal strategy exists in all cases, and the value of this strategy is the unique solution of a nonlinear equation involving the transition function of the Markov chain.
Kesten, Harry, Spitzer, Frank
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Variance and Covariance of Several Simultaneous Outputs of a Markov Chain [PDF]
Discrete Mathematics & Theoretical Computer Science, 2016 The partial sum of the states of a Markov chain or more generally a Markov source is asymptotically normally distributed under suitable conditions. One of these conditions is that the variance is unbounded.
Sara Kropf
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Approximating Markov chains. [PDF]
Proceedings of the National Academy of Sciences, 1992 A common framework of finite state approximating Markov chains is developed for discrete time deterministic and stochastic processes. Two types of approximating chains are introduced: (i) those based on stationary conditional probabilities (time averaging) and (ii) transient, based on the percentage of the Lebesgue measure of the image of cells ...
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Digital Cognitive Phenotyping for Differential Diagnosis and Monitoring in Neurological Conditions
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To assess the utility, accessibility, and equivalence to supervised scales of online cognitive assessment in older individuals with cognitive impairment. Methods Patients with Alzheimer's disease (AD, n = 31), idiopathic normal pressure hydrocephalus (iNPH, n = 26), and traumatic brain injury (TBI, n = 23) completed online cognitive ...
Martina Del Giovane +10 more
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npj Systems Biology and ApplicationsComprehensive analysis of the dynamics of Boolean models of biological systems is hampered by the exponentially large state space. Here we introduce the succession-diagram-based Markov chain (SD Markov chain), a coarse-grained representation that uses ...
Kyu Hyong Park, Réka Albert
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Stochastic Processes and their ApplicationsThe Importance Markov chain is a novel algorithm bridging the gap between rejection sampling and importance sampling, moving from one to the other through a tuning parameter. Based on a modified sample of an instrumental Markov chain targeting an instrumental distribution (typically via a MCMC kernel), the Importance Markov chain produces an extended ...
Andral, Charly +3 more
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Conditioning an additive functional of a markov chain to stay non-negative. I, Survival for a long time [PDF]
, 2005 Let (X-t)(t >= 0) be a continuous-time irreducible Markov chain on a finite state space E, let v be a map v: E -> R \ {0}, and let (phi(t))(t >= 0) be an additive functional defined by phi(t) = integral(0)(t)(X-s) ds.
Warren, Jon +2 more
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Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Advanced Engineering Materials, EarlyView.Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
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A New Improved Parsimonious Multivariate Markov Chain Model
Journal of Applied Mathematics, 2013 We present a new improved parsimonious multivariate Markov chain model. Moreover, we find a new convergence condition with a new variability to improve the prediction accuracy and minimize the scale of the convergence condition.
Chao Wang, Ting-Zhu Huang
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