32 citations · 33 across the 2 of their papers we have counts for
2 papers
stat.ME2020★ 1 cited
Non-Separable Spatio-temporal Models via Transformed Gaussian Markov Random Fields
Douglas R. M. Azevedo, Marcos O. Prates, Michael R. Willig
Models that capture the spatial and temporal dynamics are applicable in many science fields. Non-separable spatio-temporal models were introduced in the literature to capture these…
stat.ME2012★ 32 cited
Transformed Gaussian Markov Random Fields and Spatial Modeling
Marcos O. Prates, Dipak K. Dey, Michael R. Willig +1
The Gaussian random field (GRF) and the Gaussian Markov random field (GMRF) have been widely used to accommodate spatial dependence under the generalized linear mixed model framewo…