Cargando…
Bayesian Dynamical Systems Modelling in the Social Sciences
Data arising from social systems is often highly complex, involving non-linear relationships between the macro-level variables that characterize these systems. We present a method for analyzing this type of longitudinal or panel data using differential equations. We identify the best non-linear func...
Autores principales: | Ranganathan, Shyam, Spaiser, Viktoria, Mann, Richard P., Sumpter, David J. T. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3896482/ https://www.ncbi.nlm.nih.gov/pubmed/24466110 http://dx.doi.org/10.1371/journal.pone.0086468 |
Ejemplares similares
-
The Dynamics of Democracy, Development and Cultural Values
por: Spaiser, Viktoria, et al.
Publicado: (2014) -
Choice modelling with Gaussian processes in the social sciences: A case study of neighbourhood choice in Stockholm
por: Mann, Richard P., et al.
Publicado: (2018) -
Understanding Democracy and Development Traps Using a Data-Driven Approach
por: Ranganathan, Shyam, et al.
Publicado: (2015) -
Using Bayesian dynamical systems, model averaging and neural networks to determine interactions between socio-economic indicators
por: Blomqvist, Björn R. H., et al.
Publicado: (2018) -
Setting development goals using stochastic dynamical system models
por: Ranganathan, Shyam, et al.
Publicado: (2017)