About: Telescoping Markov chain

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In probability theory, a telescoping Markov chain (TMC) is a vector-valued stochastic process that satisfies a Markov property and admits a hierarchical format through a network of transition matrices with cascading dependence. For any consider the set of spaces . The hierarchical process defined in the product-space is said to be a TMC if there is a set of transition probability kernels such that * v * t * e

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  • In probability theory, a telescoping Markov chain (TMC) is a vector-valued stochastic process that satisfies a Markov property and admits a hierarchical format through a network of transition matrices with cascading dependence. For any consider the set of spaces . The hierarchical process defined in the product-space is said to be a TMC if there is a set of transition probability kernels such that 1. * is a Markov chain with transition probability matrix 2. * there is a cascading dependence in every level of the hierarchy, for all 3. * satisfies a Markov property with a transition kernel that can be written in terms of the 's,where and * v * t * e (en)
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  • In probability theory, a telescoping Markov chain (TMC) is a vector-valued stochastic process that satisfies a Markov property and admits a hierarchical format through a network of transition matrices with cascading dependence. For any consider the set of spaces . The hierarchical process defined in the product-space is said to be a TMC if there is a set of transition probability kernels such that * v * t * e (en)
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  • Telescoping Markov chain (en)
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