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首页> 外文期刊>Brazilian Journal of Probability and Statistics >Predicting dependent binary outcomes through logistic regressions and meta-elliptical copulas
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Predicting dependent binary outcomes through logistic regressions and meta-elliptical copulas

机译：通过逻辑回归和亚椭圆关联函数预测相关的二元结果

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The authors consider copula models for vectors of binary response variables having marginal distributions that depend on covariates through logistic regressions. They show how to test for residual pairwise dependence between responses, given the explanatory variables. The procedure they propose is based on the score statistic derived from the assumed copula structure under the alternative. The authors further argue that conditional dependence can be conveniently modelled with meta-elliptical copulas, which offer a wide range of positive and negative degrees of association. They call on a composite likelihood to estimate the copula parameters and they provide standard error estimates of the same via linearization. They illustrate their results with Canadian data on the presence or absence of various log grades in trees.
机译：作者考虑了具有二进制分布的二进制响应变量向量的copula模型，该分布的边际分布依赖于通过逻辑回归的协变量。他们给出了解释变量，展示了如何测试响应之间的剩余成对依赖性。他们提出的程序是基于替代方案下假设的copula结构得出的评分统计数据。作者进一步指出，条件依赖可以方便地用亚椭圆形copulas建模，后者提供了广泛的正负关联度。他们要求通过合成似然来估计copula参数，并通过线性化提供相同的标准误差估计。他们用有关树木中各种原木等级存在或不存在的加拿大数据来说明其结果。

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