## Not run: ------------------------------------
# ## Get newest version of BayesXsrc.
# ## Note: needs sh, svn and R build tools!
# get_BayesXsrc()
#
# if(require("BayesXsrc")) {
# ## Simulate some data
# set.seed(123)
# d <- GAMart()
#
# ## Estimate model with BayesX. Note
# ## that BayesX computes starting values, so
# ## these are not required by some optimizer function
# ## in bamlss()
# b1 <- bamlss(num ~ s(x1) + s(x2) + s(x3) + s(lon,lat),
# data = d, optimizer = FALSE, sampler = BayesX)
#
# plot(b1)
#
# ## Same model with anisotropic penalty.
# b2 <- bamlss(num ~ s(x1) + s(x2) + s(x3) + tx(lon,lat),
# data = d, optimizer = FALSE, sampler = BayesX)
#
# plot(b2)
#
# ## Quantile regression.
# b3_0.1 <- bamlss(num ~ s(x1) + s(x2) + s(x3) + tx(lon,lat),
# data = d, optimizer = FALSE, sampler = BayesX,
# family = gF("quant", prob = 0.1))
#
# b3_0.9 <- bamlss(num ~ s(x1) + s(x2) + s(x3) + tx(lon,lat),
# data = d, optimizer = FALSE, sampler = BayesX,
# family = gF("quant", prob = 0.9))
#
# ## Predict quantiles.
# p_0.1 <- predict(b3_0.1, term = "s(x2)")
# p_0.9 <- predict(b3_0.9, term = "s(x2)")
#
# ## Plot.
# plot2d(p_0.1 + p_0.9 ~ x2, data = d)
# }
## ---------------------------------------------
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