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Regression in a copula model for bivariate count data

机译:copula模型中双变量计数数据的回归

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In many cases of modeling bivariate count data, the interest lies on studying the association rather than the marginal properties. We form a flexible regression copula-based model where covariates are used not only for the marginal but also for the copula parameters. Since copula measures the association, the use of covariates in its parameters allow for direct modeling of association. A real-data application related to transaction market basket data is used. Our goal is to refine and understand whether the association between the number of purchases of certain product categories depends on particular demographic customers' characteristics. Such information is important for decision making for marketing purposes.
机译:在对双变量计数数据建模的许多情况下,关注点在于研究关联而不是边际属性。我们形成了一个灵活的基于copula回归的模型,其中协变量不仅用于边际,还用于copula参数。由于copula可以测量关联,因此在其参数中使用协变量可以直接建立关联模型。使用与交易市场篮子数据相关的实际数据应用程序。我们的目标是完善和了解某些产品类别的购买数量之间的关联是否取决于特定的人口统计客户的特征。此类信息对于出于营销目的的决策至关重要。

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