Pseudo-likelhood ratio tests for semiparametric multivariate copula model selection
Pseudo-likelhood ratio tests for semiparametric multivariate copula model selection
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DOI：
10.1002/cjs.5540330306
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发表时间：
2005-09-01
影响因子：
0.6
通讯作者：
Fan, YQ
中科院分区：
文献类型：
--
作者：
Chen, XH;Fan, YQ
作者提出了伪似然比检验选择半参数多变量copula模型，其中的边际分布是未指定的，但copula函数是参数化的，可以被错误指定。对于两个模型的比较，检验的不同取决于两个Copula是广义非嵌套还是广义嵌套。对于两个以上的模型，该程序是建立在现实检查测试的白色（2000）。然而，与白色（2000）不同的是，检验统计量自动标准化为广义非嵌套模型（与基准），并渐近忽略广义嵌套模型。作者用美国保险索赔数据说明了他们的方法。
The authors propose pseudo-likelihood ratio tests for selecting semiparametric multivariate copula models in which the marginal distributions are unspecified, but the copula function is parameterized and can be misspecified. For the comparison of two models, the tests differ depending on whether the two copulas are generalized nonnested or generalized nested. For more than two models, the procedure is built on the reality check test of White (2000). Unlike White (2000), however, the test statistic is automatically standardized for generalized nonnested models (with the benchmark) and ignores generalized nested models asymptotically. The authors illustrate their approach with American insurance claim data.