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Using Bayesian dynamical systems, model averaging and neural networks to determine interactions between socio-economic indicators
Social and economic systems produce complex and nonlinear relationships in the indicator variables that describe them. We present a Bayesian methodology to analyze the dynamical relationships between indicator variables by identifying the nonlinear functions that best describe their interactions. We...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5942783/ https://www.ncbi.nlm.nih.gov/pubmed/29742126 http://dx.doi.org/10.1371/journal.pone.0196355 |