ContrivedData | R Documentation |
These data are a simulated point-referenced geospatial data that serve to provide a clean example of a kriging model. There are 500 observations with coordinates located on a unit square.
The ContrivedData
dataset has 500 observations and 5 variables.
y
The outcome variable. Its true population functional form is y_s=0+1 x_{1s}+2 x_{2s}+ω_{s}+ε_{s}. The true variance of ω is σ^2=0.5 and of ε is τ^2=0.5. The decay term that shapes spatial correlation levels is φ=2.5.
x.1
A predictor with a standard uniform distribution.
x.2
A predictor with a standard normal distribution.
s.1
Coordinate in eastings for each observation, distributed standard uniform.
s.2
Coordinate in northings for each observation, distributed standard uniform.
## Not run: # Summarize example data summary(ContrivedData) # Initial OLS model contrived.ols<-lm(y~x.1+x.2,data=ContrivedData) # summary(contrived.ols) # Set seed set.seed(1241060320) #For simple illustration, we set to few iterations. #In this case, a 10,000-iteration run converges to the true parameters. #If you have considerable time and hardware, delete the # on the next line. #10,000 iterations took 39 min. with 8 GB RAM & a 1.5 GHz Quad-Core processor. M <- 100 #M<-10000 contrived.run <- metropolis.krige(y ~ x.1 + x.2, coords = c("s.1","s.2"), data = ContrivedData, n.iter = M, n.burnin=20, range.tol = 0.05) # Alternatively, use burnin() after estimation #contrived.run <- burnin(contrived.run, n.burnin=20) # Summarize the results and examine results against true coefficients summary(contrived.run) (TRUTH<-c(0.5,2.5,0.5,0,1,2)) ## End(Not run)
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