--- _id: '1168' abstract: - lang: eng text: Optimum experimental design theory has recently been extended for parameter estimation in copula models. The use of these models allows one to gain in flexibility by considering the model parameter set split into marginal and dependence parameters. However, this separation also leads to the natural issue of estimating only a subset of all model parameters. In this work, we treat this problem with the application of the (Formula presented.)-optimality to copula models. First, we provide an extension of the corresponding equivalence theory. Then, we analyze a wide range of flexible copula models to highlight the usefulness of (Formula presented.)-optimality in many possible scenarios. Finally, we discuss how the usage of the introduced design criterion also relates to the more general issue of copula selection and optimal design for model discrimination. acknowledgement: 'This work has been supported by the project ANR-2011-IS01-001-01 “DESIRE” and Austrian Science Fund (FWF) I833-N18. Open access funding is provided by the Austrian Science Fund (FWF). ' article_processing_charge: No author: - first_name: Elisa full_name: Perrone, Elisa id: 2A5F8724-F248-11E8-B48F-1D18A9856A87 last_name: Perrone orcid: 0000-0003-0370-9835 - first_name: Andreas full_name: Rappold, Andreas last_name: Rappold - first_name: Werner full_name: Müller, Werner last_name: Müller citation: ama: Perrone E, Rappold A, Müller W. D inf s optimality in copula models. Statistical Methods and Applications. 2017;26(3):403-418. doi:10.1007/s10260-016-0375-6 apa: Perrone, E., Rappold, A., & Müller, W. (2017). D inf s optimality in copula models. Statistical Methods and Applications. Springer. https://doi.org/10.1007/s10260-016-0375-6 chicago: Perrone, Elisa, Andreas Rappold, and Werner Müller. “D Inf s Optimality in Copula Models.” Statistical Methods and Applications. Springer, 2017. https://doi.org/10.1007/s10260-016-0375-6. ieee: E. Perrone, A. Rappold, and W. Müller, “D inf s optimality in copula models,” Statistical Methods and Applications, vol. 26, no. 3. Springer, pp. 403–418, 2017. ista: Perrone E, Rappold A, Müller W. 2017. D inf s optimality in copula models. Statistical Methods and Applications. 26(3), 403–418. mla: Perrone, Elisa, et al. “D Inf s Optimality in Copula Models.” Statistical Methods and Applications, vol. 26, no. 3, Springer, 2017, pp. 403–18, doi:10.1007/s10260-016-0375-6. short: E. Perrone, A. Rappold, W. Müller, Statistical Methods and Applications 26 (2017) 403–418. date_created: 2018-12-11T11:50:31Z date_published: 2017-08-01T00:00:00Z date_updated: 2023-09-20T11:25:09Z day: '01' ddc: - '519' department: - _id: CaUh doi: 10.1007/s10260-016-0375-6 external_id: isi: - '000407973200004' file: - access_level: open_access checksum: 0b2d1b647ca96e9ef13a14b8b6775e0f content_type: application/pdf creator: system date_created: 2018-12-12T10:16:13Z date_updated: 2020-07-14T12:44:37Z file_id: '5199' file_name: IST-2017-739-v1+2_10260_2016_375_MOESM1_ESM.pdf file_size: 56664 relation: main_file - access_level: open_access checksum: 3321ef34e02e28acfc427f77cf32812a content_type: application/pdf creator: system date_created: 2018-12-12T10:16:14Z date_updated: 2020-07-14T12:44:37Z file_id: '5200' file_name: IST-2017-739-v1+3_s10260-016-0375-6.pdf file_size: 688953 relation: main_file file_date_updated: 2020-07-14T12:44:37Z has_accepted_license: '1' intvolume: ' 26' isi: 1 issue: '3' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '08' oa: 1 oa_version: Submitted Version page: 403 - 418 publication: Statistical Methods and Applications publication_status: published publisher: Springer publist_id: '6189' pubrep_id: '739' quality_controlled: '1' scopus_import: '1' status: public title: D inf s optimality in copula models tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 26 year: '2017' ...