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.
ఈ కథనాన్ని భాగస్వామ్యం చేయండి
English 
Spanish 
Chinese 
Russian 
German 
French 
Japanese 
Portuguese 
Hindi 