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arxiv: 1506.08191 · v2 · pith:4KXJGXEHnew · submitted 2015-06-26 · 🧮 math.PR

Concentration for Poisson functionals: component counts in random geometric graphs

classification 🧮 math.PR
keywords mathbbinequalitiespoissonboundscomponentconcentrationdecayeven
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Upper bounds for the probabilities $\mathbb{P}(F\geq \mathbb{E} F + r)$ and $\mathbb{P}(F\leq \mathbb{E} F - r)$ are proved, where $F$ is a certain component count associated with a random geometric graph built over a Poisson point process on $\mathbb{R}^d$. The bounds for the upper tail decay exponentially, and the lower tail estimates even have a Gaussian decay. For the proof of the concentration inequalities, recently developed methods based on logarithmic Sobolev inequalities are used and enhanced. A particular advantage of this approach is that the resulting inequalities even apply in settings where the underlying Poisson process has infinite intensity measure.

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