Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/314990 
Year of Publication: 
2024
Citation: 
[Journal:] Statistical Papers [ISSN:] 1613-9798 [Volume:] 65 [Issue:] 6 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2024 [Pages:] 3681-3711
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
In this paper we deal with parametric estimation of the copula in the case of missing data. The data items with the same pattern of complete and missing data are combined into a subset. This approach corresponds to the MCAR model for missing data. We construct a specific Cramér–von Mises statistic as a sum of such statistics for the several missing data patterns. The minimization of the statistic gives the estimators for the parameters. We prove asymptotic normality of the parameter estimators and of the Cramér–von Mises statistic.
Subjects: 
Copula
Cramér–von Mises statistic
Minimum distance estimators
Missing data
Persistent Identifier of the first edition: 
Creative Commons License: 
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Document Type: 
Article
Document Version: 
Published Version

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