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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Markov Approximation of Chains of Infinite Order in the (d)over-bar-metric

Gallo, S. [1] ; Lerasle, M. [2] ; Takahashi, D. Y. [3, 4]
Total Authors: 3
[1] Univ Fed Rio de Janeiro, Inst Matemat, Dept Metodos Estat, BR-21945970 Rio De Janeiro - Brazil
[2] Univ Nice Sophia Antipolis, CNRS, UMR 6621, Lab JA Dieudonne, F-06108 Nice 2 - France
[3] Princeton Univ, Inst Neurosci, Princeton, NJ 08540 - USA
[4] Princeton Univ, Dept Psychol, Princeton, NJ 08540 - USA
Total Affiliations: 4
Document type: Journal article
Source: Markov Processes and Related Fields; v. 19, n. 1, p. 51-82, 2013.
Web of Science Citations: 4

We obtain explicit upper bounds for the (d) over bar -distance between a chain of infinite order and its canonical k-steps Markov approximation. Our proof is entirely constructive and involves a ``coupling from the past{''} argument. The new method covers non-necessarily continuous probability kernels, and chains with null transition probabilities. These results imply in particular the Bernoulli property for these processes. (AU)

FAPESP's process: 09/09494-0 - Bootstrap and model selection for stochastic chains with memory of variable length
Grantee:Matthieu Pierre Lerasle
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 09/09809-1 - Stochastic processes with variable length memory: Monge-Kantorovich problem, bootstrap and particle systems
Grantee:Alexsandro Giacomo Grimbert Gallo
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 08/08171-0 - Modeling populations of neurons with multicomponent systems with variable range interactions
Grantee:Daniel Yasumasa Takahashi
Support Opportunities: Scholarships in Brazil - Post-Doctoral