Running ‘RFsimulate.R’ [30m/16m]
  Running ‘krige.R’ [11s/11s]
  Running ‘lgcp.R’ [62s/39s]
  Running ‘lgm.R’ [36s/33s]
  Running ‘lgmRaster.R’ [30m/16m]
  Running ‘likfitLgm.R’ [11s/10s]
  Running ‘matern.R’
  Running ‘maternGmrfPrec.R’ [32m/24m]
  Running ‘profLlgm.R’ [0m/32m]
  Running ‘simLgcp.R’ [0s/19s]
  Running ‘stackRasterList.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 
    0.363   0.005   0.369 
  > 
  > 
  > system.time({theNNadj = NNmat(N=myr, nearest=params['shape']+1, adjustEdges=TRUE)})
     user  system elapsed 
    0.123   0.014   0.137 
  > # and with the adjustment
  > system.time({precMatCorr =maternGmrfPrec(N=theNNadj, param=params, 
  + 					adjustEdges=TRUE)}) 
Running the tests in ‘tests/profLlgm.R’ failed.
Complete output:
  > 
  > library('geostatsp')
  Loading required package: Matrix
  Loading required package: terra
  terra 1.8.29
  > data('swissRain')
  > swissRain = unwrap(swissRain)
  > swissAltitude = unwrap(swissAltitude)
  > 
  > Ncores = c(1,2)[1+(.Platform$OS.type=='unix')]
  > 
  > 
  > 
  > sr2 = swissRain
  > sr2$elev = extract(swissAltitude, sr2)
  Warning message:
  [`[[<-`] only using the first column 
  > swissFit = likfitLgm(
  +     data=sr2, 
  +     formula=rain~ elev,
  +     param=c(range=10000,shape=1,nugget=0,boxcox=0.5,anisoRatio=2,anisoAngleDegrees=45),
  +     paramToEstimate = c("range",'anisoAngleDegrees','anisoRatio'),
  +     reml=FALSE,
  +     verbose=FALSE
  + )
  > 
  > 
  > # calculate log-likelihood at the MLE's, but re-estimate variance
  > sl = loglikLgm(
  +     swissFit$param[c('range','shape','boxcox', 'anisoRatio', 'anisoAngleRadians')],
  +     data=sr2, 
  +     formula=rain~ elev,
  +     reml=swissFit$model$reml)  
  > 
  > 
  > # calculate log-likelihood without re-estimating variance
  > sigSqHat = attributes(sl)$totalVarHat
  > sl1 = loglikLgm(
  +     c(attributes(sl)$param[
  +             c('boxcox','anisoRatio','anisoAngleRadians','shape', 'range')], 
  +         variance=sigSqHat),
  +     data=sr2, 
  +     formula=rain~ elev,
  +     reml=swissFit$model$reml)  
  >  
  > 
  > # re=estimate the anisotropy parameters but not the range
  > sf2 = likfitLgm(
  +     data=swissFit$data, 
  +     formula=swissFit$model$formula,
  +     param= swissFit$param[c('range','nugget','shape','boxcox', 'anisoRatio', 'anisoAngleRadians')],
  +     paramToEstimate = c('variance','anisoAngleRadians','anisoRatio'),
  +     reml=swissFit$model$reml)  
  > 
  > # these should all be the same
  > as.numeric(sl1)
  [1] 644.4812
  > as.numeric(sl) 
  [1] 644.4812
  > swissFit$optim$logL
  m2logL.ml   logL.ml 
   644.4812 -322.2406 
  > sf2$optim$logL
  m2logL.ml   logL.ml 
   644.4812 -322.2406 
  > 
  > date()
  [1] "Tue Mar  4 13:36:11 2025"
  > x=profLlgm(swissFit, mc.cores=Ncores,
  +     range=seq(15000, 55000 , len=12)
  + )
  
  Execution halted
Running the tests in ‘tests/simLgcp.R’ failed.
Complete output:
  > 
  > if(requireNamespace("INLA", quietly=TRUE) ) {
  +   INLA::inla.setOption(num.threads=2)
  +   # not all versions of INLA support blas.num.threads
  +   try(INLA::inla.setOption(blas.num.threads=2), silent=TRUE)
  + } 
  > 
  > library('geostatsp')
  Loading required package: Matrix
  Loading required package: terra