Cox process representation and inference for stochastic reaction–diffusion processes
Stochastic reaction-diffusion systems are used for modelling spatial dynamics in many disciplines, but parameter inference and model selection remain challenging. Here the authors offer a solution enabled by a connection between reaction-diffusion and the well-studied spatio-temporal Cox processes.
Guardado en:
Autores principales: | , , |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2016
|
Materias: | |
Acceso en línea: | https://doaj.org/article/a5bdcffd971d4304ad4199e51fae2167 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
id |
oai:doaj.org-article:a5bdcffd971d4304ad4199e51fae2167 |
---|---|
record_format |
dspace |
spelling |
oai:doaj.org-article:a5bdcffd971d4304ad4199e51fae21672021-12-02T17:32:08ZCox process representation and inference for stochastic reaction–diffusion processes10.1038/ncomms117292041-1723https://doaj.org/article/a5bdcffd971d4304ad4199e51fae21672016-05-01T00:00:00Zhttps://doi.org/10.1038/ncomms11729https://doaj.org/toc/2041-1723Stochastic reaction-diffusion systems are used for modelling spatial dynamics in many disciplines, but parameter inference and model selection remain challenging. Here the authors offer a solution enabled by a connection between reaction-diffusion and the well-studied spatio-temporal Cox processes.David SchnoerrRamon GrimaGuido SanguinettiNature PortfolioarticleScienceQENNature Communications, Vol 7, Iss 1, Pp 1-11 (2016) |
institution |
DOAJ |
collection |
DOAJ |
language |
EN |
topic |
Science Q |
spellingShingle |
Science Q David Schnoerr Ramon Grima Guido Sanguinetti Cox process representation and inference for stochastic reaction–diffusion processes |
description |
Stochastic reaction-diffusion systems are used for modelling spatial dynamics in many disciplines, but parameter inference and model selection remain challenging. Here the authors offer a solution enabled by a connection between reaction-diffusion and the well-studied spatio-temporal Cox processes. |
format |
article |
author |
David Schnoerr Ramon Grima Guido Sanguinetti |
author_facet |
David Schnoerr Ramon Grima Guido Sanguinetti |
author_sort |
David Schnoerr |
title |
Cox process representation and inference for stochastic reaction–diffusion processes |
title_short |
Cox process representation and inference for stochastic reaction–diffusion processes |
title_full |
Cox process representation and inference for stochastic reaction–diffusion processes |
title_fullStr |
Cox process representation and inference for stochastic reaction–diffusion processes |
title_full_unstemmed |
Cox process representation and inference for stochastic reaction–diffusion processes |
title_sort |
cox process representation and inference for stochastic reaction–diffusion processes |
publisher |
Nature Portfolio |
publishDate |
2016 |
url |
https://doaj.org/article/a5bdcffd971d4304ad4199e51fae2167 |
work_keys_str_mv |
AT davidschnoerr coxprocessrepresentationandinferenceforstochasticreactiondiffusionprocesses AT ramongrima coxprocessrepresentationandinferenceforstochasticreactiondiffusionprocesses AT guidosanguinetti coxprocessrepresentationandinferenceforstochasticreactiondiffusionprocesses |
_version_ |
1718380388210966528 |