Running ‘RFsimulate.R’ [60m/32m]
  Running ‘krige.R’ [29s/31s]
  Running ‘lgcp.R’ [99s/86s]
  Running ‘lgm.R’ [70s/68s]
  Running ‘lgmRaster.R’ [60m/36m]
  Running ‘likfitLgm.R’ [28s/35s]
  Running ‘matern.R’ [23s/25s]
  Running ‘maternGmrfPrec.R’ [0m/19m]
  Running ‘profLlgm.R’
Running the tests in ‘tests/RFsimulate.R’ failed.
Complete output:
  > library("geostatsp")
  Loading required package: Matrix
  Loading required package: terra
  terra 1.8.29
  > 
  > model <- c(var=5, range=20,shape=0.5)
  > 
  > # any old crs
  > theCrs = "+proj=utm +zone=17 +datum=NAD27 +units=m +no_defs"
  > 
  > # don't test using the randomFields package, it's currently broken on some R builds
  > options(useRandomFields = FALSE)
  > 
  >   myraster = rast(nrows=20,ncols=20,extent = ext(100,110,100,110), 
  +     crs=theCrs)
  > 
  > set.seed(0)
  > simu = RFsimulate(model = rbind(a=model, b=model+0.1), 
  +   x=myraster, n=4
  + )
Running the tests in ‘tests/lgmRaster.R’ failed.
Complete output:
  > #+ setup
  > library('geostatsp')
  Loading required package: Matrix
  Loading required package: terra
  terra 1.8.29
  > #'
  > 
  > #' # simulated data
  > 
  > # exclude this line to use the RandomFields package
  > options(useRandomFields = FALSE)
  > 
  > Ncell =  40
  > 
  > myRaster = squareRaster(ext(0,6000,0,6000), Ncell)
  > 
  > myParam=c(oneminusar=0.1, conditionalVariance=2.5^2,shape=2)
  > myQ = maternGmrfPrec(myRaster, param=myParam)
  > attributes(myQ)$info$optimalShape
       shape   variance      range   cellSize 
    4.092496 110.524266 900.000000 150.000000 
  > set.seed(0)
  > mySim = RFsimulate(attributes(myQ)$info$optimalShape, myRaster)
  install the RandomFields package for faster simulations
Running the tests in ‘tests/maternGmrfPrec.R’ failed.
Complete output:
  > library('geostatsp')
  Loading required package: Matrix
  Loading required package: terra
  terra 1.8.29
  > matrix(NNmat(7, 7)[,25], 7, 7)
       [,1] [,2] [,3] [,4] [,5] [,6] [,7]
  [1,]    0    0    0    6    0    0    0
  [2,]    0    0    5    4    5    0    0
  [3,]    0    5    3    2    3    5    0
  [4,]    6    4    2    1    2    4    6
  [5,]    0    5    3    2    3    5    0
  [6,]    0    0    5    4    5    0    0
  [7,]    0    0    0    6    0    0    0
  > 
  > myr = squareRaster(ext(0,600,0,300), 60)
  > theNN = NNmat(myr)
  > 
  > 
  > params=c(range = 6*xres(myr),
  + 		cellSize=xres(myr),
  + 		shape=2,
  + 		variance=1600)
  > 
  > 
  > # precision matrix without adjusting for edge effects
  > system.time({precMat = maternGmrfPrec(N=theNN, param=params,
  + 					adjustEdges=FALSE)})
     user  system elapsed 
    0.498   0.007   0.529 
  > 
  > 
  > system.time({theNNadj = NNmat(N=myr, nearest=params['shape']+1, adjustEdges=TRUE)})
     user  system elapsed 
    0.232   0.016   0.251 
  > # and with the adjustment
  > system.time({precMatCorr =maternGmrfPrec(N=theNNadj, param=params, 
  + 					adjustEdges=TRUE)})