Optimal designs for copula models
Copula modelling has in the past decade become a standard tool in many areas of applied statistics. However, a largely neglected aspect concerns the design of related experiments. Particularly the issue of whether the estimation of copula parameters can be enhanced by optimizing experimental conditi...
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| Format: | Online |
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Taylor & Francis
2016
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4936440/ |
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pubmed-49364402016-07-21 Optimal designs for copula models Perrone, E. Müller, W.G. Original Articles Copula modelling has in the past decade become a standard tool in many areas of applied statistics. However, a largely neglected aspect concerns the design of related experiments. Particularly the issue of whether the estimation of copula parameters can be enhanced by optimizing experimental conditions and how robust all the parameter estimates for the model are with respect to the type of copula employed. In this paper an equivalence theorem for (bivariate) copula models is provided that allows formulation of efficient design algorithms and quick checks of whether designs are optimal or at least efficient. Some examples illustrate that in practical situations considerable gains in design efficiency can be achieved. A natural comparison between different copula models with respect to design efficiency is provided as well. Taylor & Francis 2016-07-03 2016-01-08 /pmc/articles/PMC4936440/ /pubmed/27453616 http://dx.doi.org/10.1080/02331888.2015.1111892 Text en © 2016 The Author(s). Published by Taylor & Francis. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0 (http://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Perrone, E. Müller, W.G. |
| spellingShingle |
Perrone, E. Müller, W.G. Optimal designs for copula models |
| author_facet |
Perrone, E. Müller, W.G. |
| author_sort |
Perrone, E. |
| title |
Optimal designs for copula models |
| title_short |
Optimal designs for copula models |
| title_full |
Optimal designs for copula models |
| title_fullStr |
Optimal designs for copula models |
| title_full_unstemmed |
Optimal designs for copula models |
| title_sort |
optimal designs for copula models |
| description |
Copula modelling has in the past decade become a standard tool in many areas of applied statistics. However, a largely neglected aspect concerns the design of related experiments. Particularly the issue of whether the estimation of copula parameters can be enhanced by optimizing experimental conditions and how robust all the parameter estimates for the model are with respect to the type of copula employed. In this paper an equivalence theorem for (bivariate) copula models is provided that allows formulation of efficient design algorithms and quick checks of whether designs are optimal or at least efficient. Some examples illustrate that in practical situations considerable gains in design efficiency can be achieved. A natural comparison between different copula models with respect to design efficiency is provided as well. |
| publisher |
Taylor & Francis |
| publishDate |
2016 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4936440/ |
| _version_ |
1613605565356834816 |