---
_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. <i>Statistical
    Methods and Applications</i>. 2017;26(3):403-418. doi:<a href="https://doi.org/10.1007/s10260-016-0375-6">10.1007/s10260-016-0375-6</a>
  apa: Perrone, E., Rappold, A., &#38; Müller, W. (2017). D inf s optimality in copula
    models. <i>Statistical Methods and Applications</i>. Springer. <a href="https://doi.org/10.1007/s10260-016-0375-6">https://doi.org/10.1007/s10260-016-0375-6</a>
  chicago: Perrone, Elisa, Andreas Rappold, and Werner Müller. “D Inf s Optimality
    in Copula Models.” <i>Statistical Methods and Applications</i>. Springer, 2017.
    <a href="https://doi.org/10.1007/s10260-016-0375-6">https://doi.org/10.1007/s10260-016-0375-6</a>.
  ieee: E. Perrone, A. Rappold, and W. Müller, “D inf s optimality in copula models,”
    <i>Statistical Methods and Applications</i>, 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.” <i>Statistical
    Methods and Applications</i>, vol. 26, no. 3, Springer, 2017, pp. 403–18, doi:<a
    href="https://doi.org/10.1007/s10260-016-0375-6">10.1007/s10260-016-0375-6</a>.
  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:
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  date_updated: 2020-07-14T12:44:37Z
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  date_created: 2018-12-12T10:16:14Z
  date_updated: 2020-07-14T12:44:37Z
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file_date_updated: 2020-07-14T12:44:37Z
has_accepted_license: '1'
intvolume: '        26'
isi: 1
issue: '3'
language:
- iso: eng
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'
...