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arXiv math/0609801math.PR
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随机度量测度空间依分布收敛性(λ-结合测度树)

Convergence in distribution of random metric measure spaces: (Lambda-coalescent measure trees)

Andreas Greven, Peter Pfaffelhuber, Anita Winter

摘要:

我们考虑完备可分度量空间的空间,这些度量空间具有一个概率测度。基于度量测度空间序列收敛当且仅当从这些空间采样的所有有限子空间收敛的哲学,给出了收敛的概念。这个拓扑是度量化以下格罗莫夫的思想嵌入两个度量空间等距到一个共同的度量空间结合Prohorov度量之间的概率测度在一个固定的度量空间。我们表明,这种拓扑结构的依分布收敛如下-提供的序列是紧的-从所有随机采样的有限子空间的收敛。我们给出了一个表征的基础上的数量是相当容易计算的紧密性。特别感兴趣的子空间是实树空间和配备有概率测度的超度量空间。作为一个例子,我们的特点依分布收敛的(超)度量测度空间的随机谱系的λ-coalescents。我们表明,λ-coalescent定义了一个无限(随机)度量测度空间当且仅当所谓的“无尘”属性举行。

英文摘要:

We consider the space of complete and separable metric spaces which are equipped with a probability measure. A notion of convergence is given based on the philosophy that a sequence of metric measure spaces converges if and only if all finite subspaces sampled from these spaces converge. This topology is metrized following Gromov's idea of embedding two metric spaces isometrically into a common metric space combined with the Prohorov metric between probability measures on a fixed metric space. We show that for this topology convergence in distribution follows - provided the sequence is tight - from convergence of all randomly sampled finite subspaces. We give a characterization of tightness based on quantities which are reasonably easy to calculate. Subspaces of particular interest are the space of real trees and of ultra-metric spaces equipped with a probability measure. As an example we characterize convergence in distribution for the (ultra-)metric measure spaces given by the random genealogies of the Lambda-coalescents. We show that the Lambda-coalescent defines an infinite (random) metric measure space if and only if the so-called "dust-free"-property holds.

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