## ----include=TRUE, eval=FALSE-------------------------------------------------
# install.packages("spm", dependencies = c("Imports", "Suggests"))

## ----include=TRUE, eval=FALSE-------------------------------------------------
# library(spm)
# data(petrel)
# set.seed(1234)
# idwcv1 <- idwcv(petrel[, c(1,2)], petrel[, 5], nmax = 12, idp = 2, predacc = "VEcv")
# idwcv1
# [1] 23.11333

## ----include=TRUE, eval=FALSE-------------------------------------------------
# library(spm)
# data(petrel)
# set.seed(1234)
# rfokcv1 <- rfokcv(petrel[, c(1,2)], petrel[, c(1,2, 6:9)], petrel[, 5], predacc = "VEcv")
# rfokcv1
# [1] 39.88995

## ----include=TRUE, eval=FALSE-------------------------------------------------
# data(petrel)
# idp <- c((1:10)*0.2)
# nmax <- c(10:20)
# idwopt <- array(0,dim=c(length(idp),length(nmax)))
# for (i in 1:length(idp)) {
# for (j in 1:length(nmax))  {
# set.seed(1234)
# idwcv2.3 <- idwcv(petrel[, c(1,2)], petrel[, 5], nmax = nmax[j], idp = idp[i], predacc = "VEcv" )
# idwopt[i, j] <- idwcv2.3
#   }
# }
# which (idwopt == max(idwopt), arr.ind = T )
# >      row col
# [1,]   3   3
# idp[3]
# > [1] 0.6
# nmax[3]
# > [1] 12

## ----include=TRUE, eval=FALSE-------------------------------------------------
# library(spm)
# data(petrel)
# set.seed(1234)
# idwcv1 <- idwcv(petrel[, c(1,2)], petrel[, 5], nmax = 12, idp = 0.6, predacc = "VEcv")
# idwcv1
# [1] 35.93557

## ----include=TRUE, eval=FALSE-------------------------------------------------
# n <- 100 # number of iterations, 60 to 100 is recommended.
# measures <- NULL
# for (i in 1:n) {
#  idwcv1 <- idwcv(petrel [, c(1,2)], petrel [, 5], nmax = 12, idp = 0.6, predacc = "ALL")
#  measures <- rbind(measures, idwcv1$vecv)
#  }
# mean(measures)
# [1] 33.69691

## ----include=TRUE, eval=FALSE-------------------------------------------------
# library(spm)
# data(petrel)
# data(petrel.grid)
# idwpred1 <- idwpred(petrel[, c(1,2)], petrel[, 5], petrel.grid, nmax = 12, idp = 0.6)
# names(idwpred1)
# [1] "LON"       "LAT"       "var1.pred" "var1.var"
# idwpred1 <- (idwpred1)[, -4] # remove the 4th column as it contains no information.
# class(idwpred1)
# [1] "data.frame"
# names(idwpred1) <- c("longitude", "latitude", "gravel")
# head(idwpred1)
#         longitude latitude  gravel
# 470277  128.8022  -10.60239 22.00789
# 470278  128.8047  -10.60239 22.00805
# 470279  128.8072  -10.60239 22.00822
# 470280  128.8097  -10.60239 22.00838
# 470281  128.8122  -10.60239 22.00855
# 470282  128.8147  -10.60239 22.00873

## ----include=TRUE, eval=FALSE-------------------------------------------------
# set.seed(1234)
# library(spm)
# data(petrel)
# data(petrel.grid)
# data(petrel)
# data(petrel.grid)
# rfokpred1 <- rfokpred(petrel[, c(1,2)], petrel[, c(1,2, 6:9)], petrel[, 5],
#  petrel.grid[, c(1,2)], petrel.grid, ntree = 500, nmax = 11, vgm.args = ("Log"))
# class(rfokpred1)
# [1] "data.frame"
# names(rfokpred1)
# 
# [1] "LON"         "LAT"         "Predictions" "Variances"