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arxiv: 1710.08856 · v1 · pith:7Z7PNRV6new · submitted 2017-10-24 · 🧮 math.PR

Approximating conditional distributions

classification 🧮 math.PR
keywords bridgesdistanceapproximatingconditionaldistributionsmethodrandomwhose
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In this article, we discuss the basic ideas of a general procedure to adapt the Stein-Chen method to bound the distance between conditional distributions. From an integration-by-parts formula (IBPF), we derive a Stein operator whose solution can be bounded, for example, via ad hoc couplings. This method provides quantitative bounds in several examples: the filtering equation, the distance between bridges of random walks and the distance between bridges and discrete schemes approximating them. Moreover, through the coupling construction for a certain class of random walk bridges we determine samplers, whose convergence to equilibrium is computed explicitly.

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