Regression in a copula model for bivariate count data
Regression in a copula model for bivariate count data
复制标题
双变量计数数据的 copula 模型中的回归
DOI：
10.1080/02664760903093591
复制
发表时间：
2010
影响因子：
1.5
通讯作者：
D. Karlis
中科院分区：
文献类型：
--
作者：
Aristidis K. Nikoloulopoulos;D. Karlis
在对二元计数数据进行建模的许多情况下，兴趣在于研究关联而不是边缘属性。我们形成了一个灵活的回归copula为基础的模型，协变量不仅用于边际，但也为copula参数。由于Copula测量的是关联性，因此在其参数中使用协变量可以直接对关联性进行建模。使用与交易市场篮子数据相关的真实数据应用。我们的目标是细化和理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。这些信息对于营销目的的决策非常重要。
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.