Bayesian Hierarchical Model for Risk Reduction in Municipal Water Systems: Methodological Evaluation of South African Case Studies
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| Main Authors: | , , , |
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| Format: | Recurso digital |
| Language: | English |
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Zenodo
2014
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| _version_ | 1866901595444215808 |
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| author | Gill, Bethan Bull-Richardson, Laura Atkins, Zoe Hughes, Mrs Tina |
| author_facet | Gill, Bethan Bull-Richardson, Laura Atkins, Zoe Hughes, Mrs Tina |
| contents | <p>This study addresses a current research gap in Computer Science concerning Methodological evaluation of municipal water systems systems in South Africa: Bayesian hierarchical model for measuring risk reduction in South Africa. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of municipal water systems systems in South Africa: Bayesian hierarchical model for measuring risk reduction, South Africa, Africa, Computer Science, methodology paper This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19093943 |
| institution | Zenodo |
| language | eng |
| publishDate | 2014 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Bayesian Hierarchical Model for Risk Reduction in Municipal Water Systems: Methodological Evaluation of South African Case Studies Gill, Bethan Bull-Richardson, Laura Atkins, Zoe Hughes, Mrs Tina Bayesian statistics hierarchical modelling Markov chain Monte Carlo spatial analysis uncertainty quantification predictive modelling data assimilation <p>This study addresses a current research gap in Computer Science concerning Methodological evaluation of municipal water systems systems in South Africa: Bayesian hierarchical model for measuring risk reduction in South Africa. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of municipal water systems systems in South Africa: Bayesian hierarchical model for measuring risk reduction, South Africa, Africa, Computer Science, methodology paper This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.</p> |
| title | Bayesian Hierarchical Model for Risk Reduction in Municipal Water Systems: Methodological Evaluation of South African Case Studies |
| topic | Bayesian statistics hierarchical modelling Markov chain Monte Carlo spatial analysis uncertainty quantification predictive modelling data assimilation |
| url | https://doi.org/10.5281/zenodo.19093943 |