Journal of Biometrics & Biostatistics

ISSN: 2155-6180

Open Access

Spatial Gaussian Markov Random Fields: Modelling, Applications and Efficient Computations


Yu Ryan Yue and Xiao-Feng Wang

A powerful modelling tool for spatial data is the framework of Gaussian Markov random fields (GMRFs), which are discrete domain Gaussian random fields equipped with a Markov property. GMRFs allow us to combine the analytical results for the Gaussian distribution as well as Markov properties, thus allow for the development of computationally efficient algorithms. Here we briefly review popular spatial GMRFs, show how to construct them, and outline their recent developments and possible future work.


Share this article

Google Scholar citation report
Citations: 3254

Journal of Biometrics & Biostatistics received 3254 citations as per Google Scholar report

Journal of Biometrics & Biostatistics peer review process verified at publons

Indexed In

arrow_upward arrow_upward