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New measures of dumpiness for incidence data

机译：发病率数据新的度量方法

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In recent years, growing attention has been placed on the increasing pattern of 'clumpy data' in many empirical areas such as financial market microstructure, criminology and seismology, and digital media consumption to name just a few; but a well-defined and careful measurement of dumpiness has remained somewhat elusive. The related 'hot hand' effect has long been a widespread belief in sports, and has triggered a branch of interesting research which could shed some light on this domain. However, since many concerns have been raised about the low power of the existing 'hot hand' significance tests, we propose a new class of dumpiness measures which are shown to have higher statistical power in extensive simulations under a wide variety of statistical models for repeated outcomes. Finally, an empirical study is provided by using a unique dataset obtained from Hulu.com, an increasingly popular video streaming provider. Our results provide evidence that the 'clumpiness phenomena' is widely prevalent in digital content consumption, which supports the lore of 'bingeability' of online content believed to exist today.
机译：近年来，越来越多的注意力集中在许多经验领域的“笨拙数据”模式上，例如金融市场微观结构，犯罪学和地震学以及数字媒体消费等。但是对松散度的明确定义和仔细衡量仍然难以捉摸。长期以来，相关的“热手”效应一直是体育界的普遍信念，并引发了一系列有趣的研究，可能会为这一领域提供一些启示。但是，由于对现有“热手”重要性测试的低功耗提出了许多担忧，我们提出了一种新的“水度”度量标准，在多种统计模型下的大量模拟中，该度量标准显示出较高的统计能力，可以重复使用。结果。最后，通过使用从越来越流行的视频流媒体提供商Hulu.com获得的唯一数据集进行了实证研究。我们的结果提供了证据，表明“团块现象”在数字内容消费中十分普遍，这支持了对当今认为存在的在线内容的“可黏性”的绝大部分知识。

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