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Analyzing Sample Path Data from Markov Chain Sampling Experiments

In: Computations with Markov Chains

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  • George S. Fishman

    (University of North Carolina at Chapel Hill, Department of Operations Research Chapel Hill)

Abstract

The mandate from the conference chairman was to provide an introductory account of the statistical issues that arise when designing Markov chain sampling experiments and analyzing their output. However, the time limitation makes my objective in this paper considerably more modest. It is merely to provide an account of how the interaction among four design parameters affects statistiical properties of estimates of (1) $$\mu = \mu (g) = {{\smallint }_{\% }}g(x)dF(x)$$ where F denotes an m-dimensional d.f. on $$\% \subseteq {{\mathbb{R}}^{m}}$$ and g satisfies $${{\smallint }_{\% }}{{g}^{4}}(x)dF(x)

Suggested Citation

  • George S. Fishman, 1995. "Analyzing Sample Path Data from Markov Chain Sampling Experiments," Springer Books, in: William J. Stewart (ed.), Computations with Markov Chains, chapter 15, pages 237-253, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4615-2241-6_15
    DOI: 10.1007/978-1-4615-2241-6_15
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