Bayesian nonparametric dependent model for partially replicated data: The influence of fuel spills on species diversity
We introduce a dependent Bayesian nonparametric model for the probabilistic modeling of membership of subgroups in a community based on partially replicated data. The focus here is on species-by-site data, that is, community data where observations at different sites are classified in distinct speci...
| Autores principales: | , , |
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| Formato: | Journal article |
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Institute of Mathematical Statistics
2016
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| _version_ | 1826293731593027584 |
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| author | Arbel, J Mengersen, K Rousseau, J |
| author_facet | Arbel, J Mengersen, K Rousseau, J |
| author_sort | Arbel, J |
| collection | OXFORD |
| description | We introduce a dependent Bayesian nonparametric model for the probabilistic modeling of membership of subgroups in a community based on partially replicated data. The focus here is on species-by-site data, that is, community data where observations at different sites are classified in distinct species. Our aim is to study the impact of additional covariates, for instance, environmental variables, on the data structure, and in particular on the community diversity. To this end, we introduce dependence a priori across the covariates and show that it improves posterior inference. We use a dependent version of the Griffiths–Engen–McCloskey distribution defined via the stickbreaking construction. This distribution is obtained by transforming a Gaussian process whose covariance function controls the desired dependence. The resulting posterior distribution is sampled by Markov chain Monte Carlo. We illustrate the application of our model to a soil microbial data set acquired across a hydrocarbon contamination gradient at the site of a fuel spill in Antarctica. This method allows for inference on a number of quantities of interest in ecotoxicology, such as diversity or effective concentrations, and is broadly applicable to the general problem of community response to environmental variables. |
| first_indexed | 2024-03-07T03:34:41Z |
| format | Journal article |
| id | oxford-uuid:bbe1b213-0c10-425b-b4c4-f9dcbedfad37 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T03:34:41Z |
| publishDate | 2016 |
| publisher | Institute of Mathematical Statistics |
| record_format | dspace |
| spelling | oxford-uuid:bbe1b213-0c10-425b-b4c4-f9dcbedfad372022-03-27T05:20:17ZBayesian nonparametric dependent model for partially replicated data: The influence of fuel spills on species diversityJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:bbe1b213-0c10-425b-b4c4-f9dcbedfad37Symplectic Elements at OxfordInstitute of Mathematical Statistics2016Arbel, JMengersen, KRousseau, JWe introduce a dependent Bayesian nonparametric model for the probabilistic modeling of membership of subgroups in a community based on partially replicated data. The focus here is on species-by-site data, that is, community data where observations at different sites are classified in distinct species. Our aim is to study the impact of additional covariates, for instance, environmental variables, on the data structure, and in particular on the community diversity. To this end, we introduce dependence a priori across the covariates and show that it improves posterior inference. We use a dependent version of the Griffiths–Engen–McCloskey distribution defined via the stickbreaking construction. This distribution is obtained by transforming a Gaussian process whose covariance function controls the desired dependence. The resulting posterior distribution is sampled by Markov chain Monte Carlo. We illustrate the application of our model to a soil microbial data set acquired across a hydrocarbon contamination gradient at the site of a fuel spill in Antarctica. This method allows for inference on a number of quantities of interest in ecotoxicology, such as diversity or effective concentrations, and is broadly applicable to the general problem of community response to environmental variables. |
| spellingShingle | Arbel, J Mengersen, K Rousseau, J Bayesian nonparametric dependent model for partially replicated data: The influence of fuel spills on species diversity |
| title | Bayesian nonparametric dependent model for partially replicated data: The influence of fuel spills on species diversity |
| title_full | Bayesian nonparametric dependent model for partially replicated data: The influence of fuel spills on species diversity |
| title_fullStr | Bayesian nonparametric dependent model for partially replicated data: The influence of fuel spills on species diversity |
| title_full_unstemmed | Bayesian nonparametric dependent model for partially replicated data: The influence of fuel spills on species diversity |
| title_short | Bayesian nonparametric dependent model for partially replicated data: The influence of fuel spills on species diversity |
| title_sort | bayesian nonparametric dependent model for partially replicated data the influence of fuel spills on species diversity |
| work_keys_str_mv | AT arbelj bayesiannonparametricdependentmodelforpartiallyreplicateddatatheinfluenceoffuelspillsonspeciesdiversity AT mengersenk bayesiannonparametricdependentmodelforpartiallyreplicateddatatheinfluenceoffuelspillsonspeciesdiversity AT rousseauj bayesiannonparametricdependentmodelforpartiallyreplicateddatatheinfluenceoffuelspillsonspeciesdiversity |