Inferring collective dynamical states from widely unobserved systems
From infectious diseases to brain activity, complex systems can be approximated using autoregressive models. Here, the authors show that incomplete sampling can bias estimates of the stability of such systems, and introduce a novel, unbiased metric for use in such situations.
Guardado en:
Autores principales: | Jens Wilting, Viola Priesemann |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2018
|
Materias: | |
Acceso en línea: | https://doaj.org/article/82ce44a5b8ed4fe98882d364db6aa974 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Sensor Selection and State Estimation for Unobservable and Non-Linear System Models
por: Thijs Devos, et al.
Publicado: (2021) -
Model-free inference of direct network interactions from nonlinear collective dynamics
por: Jose Casadiego, et al.
Publicado: (2017) -
STATISTICAL ESTIMATION OF UNOBSERVED ECONOMIC ACTIVITY
por: Galina V. Agentova
Publicado: (2017) -
Phillips curve in Brazil: an unobserved components approach
por: Vicente da Gama Machado, et al.
Publicado: (2014) -
Post-conception heat exposure increases clinically unobserved pregnancy losses
por: Tamás Hajdu, et al.
Publicado: (2021)