Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
An autoregressive point source model for spatial processes
10.1002/env.957.abs
We suggest a parametric modeling approach for nonstationary spatial processes driven by point sources. Baseline near‐stationarity, which may be reasonable in the absence of a point source, is modeled using a conditional autoregressive (CAR) Markov random field. Variability due to the point source is captured by our proposed autoregressive point source (ARPS) model. Inference proceeds according to the Bayesian hierarchical paradigm, and is implemented using Markov chain Monte Carlo (MCMC) methods. The parametric approach allows a formal test of effectiveness of the point source. Application is made to a real dataset on electric potential measurements in a field containing a metal pole and the finding is that our approach captures the pole's impact on small‐scale variability of the electric potential process. Copyright © 2008 John Wiley & Sons, Ltd.
An autoregressive point source model for spatial processes
10.1002/env.957.abs
We suggest a parametric modeling approach for nonstationary spatial processes driven by point sources. Baseline near‐stationarity, which may be reasonable in the absence of a point source, is modeled using a conditional autoregressive (CAR) Markov random field. Variability due to the point source is captured by our proposed autoregressive point source (ARPS) model. Inference proceeds according to the Bayesian hierarchical paradigm, and is implemented using Markov chain Monte Carlo (MCMC) methods. The parametric approach allows a formal test of effectiveness of the point source. Application is made to a real dataset on electric potential measurements in a field containing a metal pole and the finding is that our approach captures the pole's impact on small‐scale variability of the electric potential process. Copyright © 2008 John Wiley & Sons, Ltd.
An autoregressive point source model for spatial processes
Hughes‐Oliver, Jacqueline M. (Autor:in) / Heo, Tae‐Young (Autor:in) / Ghosh, Sujit K. (Autor:in)
Environmetrics ; 20 ; 575-594
01.08.2009
20 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
An autoregressive point source model for spatial processes
| Online Contents | 2009
Testing for spatial autocorrelation: Moving average versus autoregressive processes
| Online Contents | 1999
Embracing heterogeneity: the spatial autoregressive mixture model
| Online Contents | 2017
Cox-type tests for competing spatial autoregressive models with spatial autoregressive disturbances
| Online Contents | 2013