MCAR (Multivariate Conditional Autoregressive) model in R - r

I am performing a spatial analysis of student grades according to their city of origin using R. I have several covariates such as poverty, education and socio-cultural indices. So far I have fitted univariate models such as: linear regression, weighted linear regression and CAR (conditional autoregressive).
Now, I am reading "Hierarchical Modeling and Analysis for Spatial Data" from Banerjee, Carlin and Gelfand. I am interested in applying multivariate models, in particular a MCAR (Multivariate Conditional Autoregressive) model.
However, I have not found any code in R (or Python) that has it implemented. The most possible has been the "spatialreg" library that includes univariate CAR and SAR models.
Is there any library that you know of that includes them? Thanks in advance


I have found "CARBayes" package. This works perfectly for fitting MCAR model.

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I have a data frame that looks like this:
df1<-data.frame( Time=seq(as.POSIXct("2017-11-13 00:00:00",tz="UTC"),
as.POSIXct("2017-11-13 00:1:59",tz="UTC"),"sec"),
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Thank you very much in advance for your help.
Let me know if you need more information.

For resources on thinking about this type of problem you might look at chapters 17 and 19 of Koenker et al. 2018 Handbook of Quantile Regression from CRC Press. Neither chapter has nice R code to go from, but they discuss different approaches to the kind of data you're working with. lqmm does use nlme machinery, so there may be a way to customize the covariance matrices for the random effects, but I suspect it would be easiest to either ask for help from the package author or to do a deep dive into the package code to figure out how to do that.

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