Optimal design of dynamic experiments for scalar-on-function linear models with application to a biopharmaceutical study
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2021
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| _version_ | 1866913851367227392 |
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| author | Michaelides, Damianos Adamou, Maria Woods, David C. Overstall, Antony M. |
| author_facet | Michaelides, Damianos Adamou, Maria Woods, David C. Overstall, Antony M. |
| contents | A Bayesian optimal experimental design framework is developed for experiments where settings of one or more variables, referred to as profile variables, can be functions. For this type of experiment, a design consists of combinations of functions for each run of the experiment. Within a scalar-on-function linear model, profile variables are represented through basis expansions. This allows finite-dimensional representation of the profile variables and optimal designs to be found. The approach enables control over the complexity of the profile variables and model. The method is illustrated on a real application involving dynamic feeding strategies in an Ambr250 modular bioreactor system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2110_09115 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Optimal design of dynamic experiments for scalar-on-function linear models with application to a biopharmaceutical study Michaelides, Damianos Adamou, Maria Woods, David C. Overstall, Antony M. Methodology A Bayesian optimal experimental design framework is developed for experiments where settings of one or more variables, referred to as profile variables, can be functions. For this type of experiment, a design consists of combinations of functions for each run of the experiment. Within a scalar-on-function linear model, profile variables are represented through basis expansions. This allows finite-dimensional representation of the profile variables and optimal designs to be found. The approach enables control over the complexity of the profile variables and model. The method is illustrated on a real application involving dynamic feeding strategies in an Ambr250 modular bioreactor system. |
| title | Optimal design of dynamic experiments for scalar-on-function linear models with application to a biopharmaceutical study |
| topic | Methodology |
| url | https://arxiv.org/abs/2110.09115 |