Skip to main content

Some diagnostics for Markov random fields

Journal Article


Download full-text (Open Access)

Abstract


  • The development of diagnostics to check the fit of a proposed Markov random field (MRP) to data is a very important problem in spatial statistics. In this article, the consequences of fitting a given MRF to spatial data are visualized using diagnostic plots. The Gaussian MRF known as the conditional autoregressive model is featured. Various types of departures of the data from the fitted MRF model are calculated, allowing locally influential observations to be highlighted using the MRF-Neighborhoods plot. Through a global summary statistic and the Model-Comparison plot, we compare MRF models that differ both in terms of the neighborhood structure and the parameterization of spatial dependence. © 2008 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

Publication Date


  • 2008

Citation


  • Cressie, N. A. & Kapat, P. (2008). Some diagnostics for Markov random fields. Journal of Computational and Graphical Statistics, 17 (3), 726-749.

Scopus Eid


  • 2-s2.0-53549101675

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=9678&context=infopapers

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/2342

Number Of Pages


  • 23

Start Page


  • 726

End Page


  • 749

Volume


  • 17

Issue


  • 3

Abstract


  • The development of diagnostics to check the fit of a proposed Markov random field (MRP) to data is a very important problem in spatial statistics. In this article, the consequences of fitting a given MRF to spatial data are visualized using diagnostic plots. The Gaussian MRF known as the conditional autoregressive model is featured. Various types of departures of the data from the fitted MRF model are calculated, allowing locally influential observations to be highlighted using the MRF-Neighborhoods plot. Through a global summary statistic and the Model-Comparison plot, we compare MRF models that differ both in terms of the neighborhood structure and the parameterization of spatial dependence. © 2008 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

Publication Date


  • 2008

Citation


  • Cressie, N. A. & Kapat, P. (2008). Some diagnostics for Markov random fields. Journal of Computational and Graphical Statistics, 17 (3), 726-749.

Scopus Eid


  • 2-s2.0-53549101675

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=9678&context=infopapers

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/2342

Number Of Pages


  • 23

Start Page


  • 726

End Page


  • 749

Volume


  • 17

Issue


  • 3