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.
Original language | English |
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Pages (from-to) | 2742-2775 |
Number of pages | 34 |
Journal | Annals of Statistics |
Volume | 32 |
Issue number | 6 |
DOIs | |
State | Published - Dec 2004 |
Keywords
- Data approximation
- Hidden Markov chains
- Markov chains
- Nonhomogenous Markov chains