2014/08/17 by Patrick Rubin‐Delanchy, Rubin-Delanchy, Patrick, Nicholas A. Heard +1
Computer Science · Mathematics · #62F03 #62F05 #62M10 #62N03 #62P30 #62P35 #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Methods and Inference #Stochastic processes and statistical mechanics
paper · pdf · doi:10.48550/arxiv.1408.3845
openalex publication_date 2014/08/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Many scientific questions rely on determining whether two sequences of event times are associated. This article introduces a likelihood ratio test which can be parameterised in several ways to detect different forms of dependence. A common finite-sample distribution is derived, and shown to be asymptotically related to a weighted Kolmogorov-Smirnov test. Analysis leading to these results also motivates a more general tool for diagnosing dependence. The methodology is demonstrated on data generated on an email network, showing evidence of information flow using only timing information. Implementation code is available in the R package `mppa'.