Results 131 to 140 of about 407,439 (176)
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Nature Methods, 2019
You can look back there to explain things, but the explanation disappears. You’ll never find it there. Things are not explained by the past. They’re explained by what happens now.
Jasleen K. Grewal +2 more
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You can look back there to explain things, but the explanation disappears. You’ll never find it there. Things are not explained by the past. They’re explained by what happens now.
Jasleen K. Grewal +2 more
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Theory of Probability & Its Applications, 1961
This paper discusses some new results related to ergodic and limit theorems and also to the repeated logarithm low for inhomogeneous Markov chains. Theorems are formulated and proved for conditions that were not treated in the literature; some estimates obtained previously by S. N. Bernshtein are employed.Lemma 1 is of greatest importance in the paper.
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This paper discusses some new results related to ergodic and limit theorems and also to the repeated logarithm low for inhomogeneous Markov chains. Theorems are formulated and proved for conditions that were not treated in the literature; some estimates obtained previously by S. N. Bernshtein are employed.Lemma 1 is of greatest importance in the paper.
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1992
Abstract In Section 7.3, we briefly introduced models for Markov chains in the simple case where there were only two possible responses: an event occurs or not. However, such models have much wider application. In continuous time models, where each subject is in one of several possible states at any given point, they are often called ...
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Abstract In Section 7.3, we briefly introduced models for Markov chains in the simple case where there were only two possible responses: an event occurs or not. However, such models have much wider application. In continuous time models, where each subject is in one of several possible states at any given point, they are often called ...
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2005
Abstract Useful models of the real world have to satisfy two conflicting requirements: they must be sufficiently complicated to describe complex systems, but they must also be sufficiently simple for us to analyse them. This chapter introduces Markov chains, which have successfully modelled a huge range of scientific and social phenomena,
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Abstract Useful models of the real world have to satisfy two conflicting requirements: they must be sufficiently complicated to describe complex systems, but they must also be sufficiently simple for us to analyse them. This chapter introduces Markov chains, which have successfully modelled a huge range of scientific and social phenomena,
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Markov Chains and Monte Carlo Markov Chains
2013The theory of Markov chains is rooted in the work of Russian mathematician Andrey Markov, and has an extensive body of literature to establish its mathematical foundations. The availability of computing resources has recently made it possible to use Markov chains to analyze a variety of scientific data, and Monte Carlo Markov chains are now one of the ...
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