#geoR: Exact interpolation: #First with nugget=0: a <- read.table("http://www.stat.ucla.edu/~nchristo/statistics_c173_c273/kriging_11.txt", header=TRUE) library(geoR) b <- as.geodata(a) q <- ksline(b, cov.model="exp", cov.pars=c(10,3.33), nugget=0, locations=c(61,139)) q$predict q$krige.var #Then with nugget=2: a <- read.table("http://www.stat.ucla.edu/~nchristo/statistics_c173_c273/kriging_11.txt", header=TRUE) library(geoR) b <- as.geodata(a) q <- ksline(b, cov.model="exp", cov.pars=c(10,3.33), nugget=2, locations=c(61,139)) q$predict q$krige.var ========================================================================= #gstat: Exact interpolation: #First with nugget=0: a <- read.table("http://www.stat.ucla.edu/~nchristo/statistics_c173_c273/kriging_11.txt", header=TRUE) library(gstat) x.range <- as.integer(range(a[,1])) y.range <- as.integer(range(a[,2])) grd <- expand.grid(x=seq(from=x.range[1], to=x.range[2], by=1), y=seq(from=y.range[1], to=y.range[2], by=1)) m <- vgm(10, "Exp", 3.33, 0) q1 <- krige(id="z", formula=z~1, data=a, newdata=grd, model = m, locations=~x+y) q1 #Then with nugget=2: m <- vgm(10, "Exp", 3.33, 2) q1 <- krige(id="z", formula=z~1, data=a, newdata=grd, model = m, locations=~x+y) q1