Laws of the iterated logarithm for symmetric jump processes
classification
🧮 math.PR
keywords
processesbetaiteratedjumplawslilslogarithmsymmetric
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Based on two-sided heat kernel estimates for a class of symmetric jump processes on metric measure spaces, the laws of the iterated logarithm (LILs) for sample paths, local times and ranges are established. In particular, the LILs are obtained for $\beta$-stable-like processes on $\alpha$-sets with $\beta>0$.
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