近年來，Copula 成為建構多元模型相當流行的方法，且被廣泛地應用在各個領域。雖然 Copula 方法可輕易的建構多元模型，但若假設的模型與真實的分配不合時，則根據此 Copula 模型得到的統計推論是否正確，則尚未有研究探討。 本文主要的目的是，針對二元非負資料，探討 Copula 模型，在模型假設不正確下，此實作模型的推論結果是否有強韌性，並與多元負二項模型之結果作一對比。 In recent years, copula models have become a popular method for modeling correlated data, and have been widely applied in many field of studies. Although one can use the copula models to construct multivariate distribution easily, there is no research discussing the robustness of copula models so far. The purpose of this thesis is to investigate the robustness property of the copula models under model misspecifications. We also compare copula models with the multivariate negative binomial model.
