KL-optimal experimental design for discriminating between two growth models applied to a beef farm
The body mass growth of organisms is usually represented in terms of what is known as ontogenetic growth models, which represent the relation of dependence between the mass of the body and time. The paper is concerned with a problem of finding an optimal experimental design for discriminating betwee...
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| Format: | Article |
| Language: | English |
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AIMS Press
2015-09-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2016.13.67 |
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| _version_ | 1832590150731825152 |
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| author | Santiago Campos-Barreiro Jesús López-Fidalgo |
| author_facet | Santiago Campos-Barreiro Jesús López-Fidalgo |
| author_sort | Santiago Campos-Barreiro |
| collection | DOAJ |
| description | The body mass growth of organisms is usually represented in terms of what is known as ontogenetic growth models, which represent the relation of dependence between the mass of the body and time. The paper is concerned with a problem of finding an optimal experimental design for discriminating between two competing mass growth models applied to a beef farm. T-optimality was first introduced for discrimination between models but in this paper, KL-optimality based on the Kullback-Leibler distance is used to deal with correlated obsevations since, in this case, observations on a particular animal are not independent. |
| format | Article |
| id | doaj-art-cf05ee751fe64c39aacd59bdac5ad1a6 |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2015-09-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-cf05ee751fe64c39aacd59bdac5ad1a62025-01-24T02:34:05ZengAIMS PressMathematical Biosciences and Engineering1551-00182015-09-01131678210.3934/mbe.2016.13.67KL-optimal experimental design for discriminating between two growth models applied to a beef farmSantiago Campos-Barreiro0Jesús López-Fidalgo1Institute of Mathematics Applied to Science and Engineering, University of Castilla-La Mancha, 13071-Ciudad RealInstitute of Mathematics Applied to Science and Engineering, University of Castilla-La Mancha, 13071-Ciudad RealThe body mass growth of organisms is usually represented in terms of what is known as ontogenetic growth models, which represent the relation of dependence between the mass of the body and time. The paper is concerned with a problem of finding an optimal experimental design for discriminating between two competing mass growth models applied to a beef farm. T-optimality was first introduced for discrimination between models but in this paper, KL-optimality based on the Kullback-Leibler distance is used to deal with correlated obsevations since, in this case, observations on a particular animal are not independent.https://www.aimspress.com/article/doi/10.3934/mbe.2016.13.67discrimination between modelskl-optimalitygrowth modelst-optimality. |
| spellingShingle | Santiago Campos-Barreiro Jesús López-Fidalgo KL-optimal experimental design for discriminating between two growth models applied to a beef farm Mathematical Biosciences and Engineering discrimination between models kl-optimality growth models t-optimality. |
| title | KL-optimal experimental design for discriminating between two growth models applied to a beef farm |
| title_full | KL-optimal experimental design for discriminating between two growth models applied to a beef farm |
| title_fullStr | KL-optimal experimental design for discriminating between two growth models applied to a beef farm |
| title_full_unstemmed | KL-optimal experimental design for discriminating between two growth models applied to a beef farm |
| title_short | KL-optimal experimental design for discriminating between two growth models applied to a beef farm |
| title_sort | kl optimal experimental design for discriminating between two growth models applied to a beef farm |
| topic | discrimination between models kl-optimality growth models t-optimality. |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2016.13.67 |
| work_keys_str_mv | AT santiagocamposbarreiro kloptimalexperimentaldesignfordiscriminatingbetweentwogrowthmodelsappliedtoabeeffarm AT jesuslopezfidalgo kloptimalexperimentaldesignfordiscriminatingbetweentwogrowthmodelsappliedtoabeeffarm |