文章基本信息

标题：Signature inversion for monotone paths
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作者：Jiawei Chang ; Nick Duffield ; Hao Ni 等
期刊名称：Electronic Communications in Probability
印刷版ISSN：1083-589X
出版年度：2017
卷号：22
DOI：10.1214/17-ECP70
语种：English
出版社：Electronic Communications in Probability
摘要：The aim of this article is to provide a simple sampling procedure to reconstruct any monotone path from its signature. For every $N$, we sample a lattice path of $N$ steps with weights given by the coefficient of the corresponding word in the signature. We show that these weights on lattice paths satisfy the large deviations principle. In particular, this implies that the probability of picking up a “wrong” path is exponentially small in $N$. The argument relies on a probabilistic interpretation of the signature for monotone paths.