| dbo:abstract |
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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dbr:Markov_property dbr:Probability_theory dbc:Markov_processes dbr:Markov_chain dbr:Stochastic_process |
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dbc:Markov_processes |
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| rdfs:comment |
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) |
| rdfs:label |
Telescoping Markov chain (en) |
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freebase:Telescoping Markov chain yago-res:Telescoping Markov chain wikidata:Telescoping Markov chain https://global.dbpedia.org/id/4w2Kx |
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wikipedia-en:Telescoping_Markov_chain?oldid=877965802&ns=0 |
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wikipedia-en:Telescoping_Markov_chain |
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