R programs that have been discussed in lab (or in class) are included here.

• Introduction to R and the sp package
• spIntro.r R code and comments for part 2 (sp package) of the R intro.
• prediction1.r R code and comments for inv. dist. weighting and trend surfaces.
• prediction2.r R code and comments for ordinary kriging 'by hand'.
• prediction3.r R code and comments for semi-variogram estimation.
• prediction4.r R code and comments for anisotropy and cross validation
• prediction5.r R code and comments for block and non-linear kriging
• plotsvmap.r (Optional) R code for simulating an isotropic Gaussian random field and plotting the variogram map. Used in 14 Feb lecture.
• areal1.r Construct neighbor lists and weight lists, compute Moran's I and Geary'c and local Moran's I
• areal2.r Fit OLS, SAR and CAR models to data. Moran's I for residuals from OLS.
• point1.r Describing spatial point processes: estimating G(x), F(x), K(x), and g(x)
• point2.r Non-CSR spatial point processes; fitting Matern Cluster and Strauss (inhibition) processes
• point3.r Estimating intensity and understanding multi-type patterns
• lin mod.r Fitting ANOVA with spatial correlation
• lin mod.sas Fitting ANOVA with spatial correlation in SAS
• papadakis.r OPTIONAL: Calculating Papadakis's covariate (average neighbor residual)
• simulate.r Simulation of Gaussian random fields using matrix operations
• simulate2.r Simulation of Gaussian random fields using functions in RandomFields