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Many scientific questions rely on determining whether two sequences of eventtimes are associated. This article introduces a likelihood ratio test which canbe parameterised in several ways to detect different forms of dependence. Acommon finite-sample distribution is derived, and shown to be asymptoticallyrelated to a weighted Kolmogorov-Smirnov test. Analysis leading to theseresults also motivates a more general tool for diagnosing dependence. Themethodology is demonstrated on data generated on an email network, showingevidence of information flow using only timing information. Implementation codeis available in the R package `mppa'.

A test for dependence between two point processes on the real line