library(gstat)
# calculate sample variogram:
v <- variogram(log(zinc) ~ 1, locations = ~ x + y, data = meuse)
# fit a model to sample variogram:
v.fit <- fit.variogram(v, model = vgm(1, "Sph", 900, 1))
# plot both:
plot(v, model = v.fit) # view result
# use ordinary kriging on a regular grid, in meuse.grid:
z <- krige(formula = log(zinc) ~ 1, locations = ~ x + y, data = meuse, 
        newdata = meuse.grid, model = v.fit) 
# view ordinary kriging prediction and prediction error
levelplot(var1.pred ~ x + y, z, aspect=mapasp(z), 
        main = "ordinary kriging prediction") # view result
levelplot(sqrt(var1.var) ~ x + y, z, aspect=mapasp(z), 
        main = "ordinary kriging prediction error") # view result