data("crd_simulated")
dados <- crd_simulated
#Geodata object
geodados <- as.geodata(dados, coords.col = 1:2, data.col = 3,
covar.col = 4)
h_max <- summary(geodados)[[3]][[2]]
dist <- 0.6*h_max
# Computing the variogram
variograma <- spVariog(geodata = geodados,
trend = "cte", max.dist = dist, design = "crd",
scale = FALSE)
plot(variograma, ylab = "Semivariance", xlab = "Distance")
# Spherical Model
ols1 <- spVariofit(variograma, cov.model = "spherical", weights = "equal",
max.dist = dist)
#Using crossvalidation to assess the error
ols1.cv <- spCrossvalid(ols1)
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