Restricting the Range

David Freedman
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David Freedman: University of California, Department of Statistics

Chapter 1 in Approximating Countable Markov Chains, 1983, pp 1-63 from Springer

Abstract: Abstract Let X be a Markov chain with state space I,stationary standard transitions P,and smooth sample functions. For simplicity, suppose I forms one recurrent class of states relative to P. Let J be a finite subset of I. Let X J be X watched only when in J; namely, X J is obtained from X by ignoring the times t with X(t) ∉ J. Call X J the restriction of X to J. This operation has been considered by Lévy (1951, 1952, 1958) and Williams (1966). The process X J is defined formally in Section 5. The idea is to introduce γ J (t),the rightmost time on the X-scale to the left of which X spends time t in J. Then X J (t)= X[γ J (t)]. Suppose J and K are finite subsets of I,with J ⊂ K. Then X J = (X K ) J as shown in Section 5. The process X J is Markov with stationary standard transitions, say P J on J. This is proved in Section 6. The semigroups {P J :J ⊂ I} are equicontinuous; consequently, X J converges to X in probability and in q-lim† with probability 1 as J increases to I ; in particular, P J converges to P as J increases to I. These results are proved in Section 7.

Keywords: Joint Distribution; Finite Subset; Sample Function; Nonnegative Number; Independent Increment (search for similar items in EconPapers)
Date: 1983
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DOI: 10.1007/978-1-4613-8230-0_1

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