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Stronger Topologies for Sample Path Large Deviations in Euclidean Space
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Abstract: In this paper we present sufficient conditions for simple path large deviation principles to be extended to finer topologies. We consider extensions of the uniform topology by Orlicz functionals and we consider Lipschitz spaces: the former are concerned with cumulative path behaviour while the latter are more sensitive to extremes in local variation. We also consider sample paths indexed by the half line, where the usual projective limit topologies are not strong enough for many applications, particularly in queueing theory.
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