Hi,

I am doing a Bayesian analysis using a spatially varying coefficient model and

I am concerned about how I can extract these spatially varying coefficients for

all 3 variables as given in example below.

It is simple to get these spatially varying coefficients from the spTDyn package

as shown below. However, the spTDyn package takes a huge amount of time

to run the model when we get a couple of more variables, and

the iteration is in thousands. I thought calling the spTDyn in the Bsptime function

computes the results much faster than spTDyn by itself? Could there be any

simple method to get these coefficients? I will then map each of the seven

spatially varying coefficients separately.

I could use the spSVC function from the spBayes package that could finish much faster than the other packages but extracting the spatially varying coefficients is still a problem. Any tips for the spSVC function would be appreciated as well.

```
library(spTDyn)
library(bmstdr)
library(spBayes)
data("nysptime")
f <- y8hrmax~ xmaxtemp + sp(xmaxtemp)+ xwdsp + sp(xwdsp) + xrh + sp(xrh)
# using the spTDyn package
model1 <- GibbsDyn(formula = f, data = nysptime, coords = ~utmx + utmy,
spatial.decay = decay(distribution = Gamm(2,1),tuning = 0.06))
# obtain parameter summary with spatially varying coefficients
summary(model1, coefficient = "spatial")
# calling the spTDyn package in Bsptime function in bmstdr package
model2 <- Bsptime(package = "sptDyn", model = "GP", formula = f, data = nysptime,
coordtype = "utm", coords = 4:5)
```

Thanks for your time and help in this regard.