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SYSTEM AND METHOD FOR MEAN ESTIMATION FOR A TORSO-HEAVY TAIL DISTRIBUTION

机译:躯干重尾分布均值估计的系统和方法

摘要

In various example embodiments, systems and methods for estimating the mean of a dataset having a fat tail. Data sets may be partitioned into components, a “torso” component and a “tail” component. For the “tail” component of the data set a more efficient estimator can be obtained (versus the traditionally calculated mean) by using the tail data to estimate parameters for a specific distribution and then deriving the mean from the estimated parameters. The estimated mean from the torso and the estimated mean from the tail may then be combined to obtain the estimated mean for the full data. This can be applied to gross merchandise bought (GMB) by various samples of visitors and apply the experience that was provided to the sample with the highest GMB to all visitors to increase gross revenue.
机译:在各种示例实施例中,用于估计具有粗尾的数据集的平均值的系统和方法。数据集可以划分为组件,“躯干”组件和“尾巴”组件。对于数据集的“尾部”部分,可以通过使用尾部数据估计特定分布的参数,然后从估计的参数中得出平均值,从而获得更有效的估计器(相对于传统计算的平均值)。然后可以组合来自躯干的估计平均值和来自尾巴的估计平均值,以获得完整数据的估计平均值。这可以应用于各种访客样本的总商品购买(GMB),并将提供给GMB最高的样本的经验应用于所有访客,以增加总收入。

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