A class of strong deviation theorems for the sequence of real valued random variables with respect to continuous-state non-homogeneous Markov chains
DOI10.1080/03610926.2020.1734838OpenAlexW3009672457MaRDI QIDQ5079146
Zhiyan Shi, Mengdi Zhao, Bei Wang, Wei-guo Yang
Publication date: 25 May 2022
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2020.1734838
strong deviation theoremlog-likelihood ratiocontinuous-state non-homogeneous Markov chainssequence of real valued random variables
Statistics (62-XX) Strong limit theorems (60F15) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10)
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Cites Work
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- Relative entropy densities and a class of limit theorems of the sequence of m-valued random variables
- A class of small deviation theorems for functionals of random fields on a homogeneous tree
- A strong limit theorem expressed by inequalities for the sequences of absolutely continuous random variables
- The Markov approximation of the sequences of \(N\)-valued random variables and a class of small deviation theorems.
- The Strong Law of Large Numbers and the Entropy Ergodic Theorem for Nonhomogeneous Bifurcating Markov Chains Indexed by a Binary Tree
- The strong law of large numbers for moving average of continuous state nonhomogeneous Markov chains
- A class of small deviation theorem for the sequences of countable state random variables with respect to homogeneous Markov chains
- A Class of Strong Deviation Theorems for the Random Fields Associated with Nonhomogeneous Markov Chains Indexed by a Bethe Tree
- A Note on some Ergodic Theorems of A. Paz
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