Approximating a sequence of observations by a simple process

Dinah Rosenberg, Nicolas Vieille () and Eilon Solan ()

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Abstract: Given an arbitrary long but finite sequence of observations from a finite set, we construct a simple process that approximates the sequence, in the sense that with high probability the empirical frequency, as well as the empirical one-step transitions along a realization from the approximating process, are close to that of the given sequence. We generalize the result to the case where the one-step transitions are required to be in given polyhedra.

Keywords: Markov chains; data approximation; nonhomogenous Markov chains; hidden Markov chains (search for similar items in EconPapers)
Date: 2004-12-01
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Citations: View citations in EconPapers (1)

Published in Annals of Statistics, 2004, Vol.32,n°6, pp.2742-2775. ⟨10.1214/009053604000000643⟩

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Working Paper: Approximating a sequence of observations by a simple process (2002)
Working Paper: Approximating a Sequence of Observations by a Simple Process (2002)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00464946

DOI: 10.1214/009053604000000643

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