CRAN Package Check Results for Package geostatsp

Last updated on 2025-03-14 18:50:54 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 2.0.8 33.51 540.84 574.35 OK
r-devel-linux-x86_64-debian-gcc 2.0.8 22.89 348.55 371.44 OK
r-devel-linux-x86_64-fedora-clang 2.0.8 948.54 OK
r-devel-linux-x86_64-fedora-gcc 2.0.8 1243.70 ERROR
r-devel-macos-arm64 2.0.8 236.00 OK
r-devel-macos-x86_64 2.0.8 634.00 OK
r-devel-windows-x86_64 2.0.8 40.00 438.00 478.00 OK
r-patched-linux-x86_64 2.0.8 NOTE
r-release-linux-x86_64 2.0.8 40.55 528.15 568.70 NOTE
r-release-macos-arm64 2.0.8 272.00 NOTE
r-release-macos-x86_64 2.0.8 716.00 NOTE
r-release-windows-x86_64 2.0.8 40.00 451.00 491.00 NOTE
r-oldrel-macos-arm64 2.0.8 253.00 NOTE
r-oldrel-macos-x86_64 2.0.8 775.00 NOTE
r-oldrel-windows-x86_64 2.0.8 52.00 601.00 653.00 NOTE

Check Details

Version: 2.0.8
Check: examples
Result: ERROR Running examples in ‘geostatsp-Ex.R’ failed The error most likely occurred in: > ### Name: RFsimulate > ### Title: Simulation of Random Fields > ### Aliases: RFsimulate modelRandomFields RFsimulate RFsimulate-methods > ### RFsimulate,ANY,SpatRaster-method RFsimulate,numeric,SpatRaster-method > ### RFsimulate,numeric,SpatVector-method > ### RFsimulate,RMmodel,SpatVector-method > ### RFsimulate,RMmodel,SpatRaster-method > ### RFsimulate,matrix,SpatRaster-method > ### RFsimulate,matrix,SpatVector-method RFsimulate,data.frame,ANY-method > ### Keywords: spatial > > ### ** Examples > > library('geostatsp') > > # exclude this line to use the RandomFields package > options(useRandomFields = FALSE) > > model1 <- c(var=5, range=1,shape=0.5) > > > myraster = rast(nrows=20,ncols=30,extent = ext(0,6,0,4), + crs="+proj=utm +zone=17 +datum=NAD27 +units=m +no_defs") > > set.seed(0) > > simu <- RFsimulate(model1, x=myraster, n=3) install the RandomFields package for faster simulations Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 2.0.8
Check: tests
Result: ERROR 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)}) Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 2.0.8
Check: package dependencies
Result: NOTE Package suggested but not available for checking: ‘RandomFields’ Package which this enhances but not available for checking: ‘INLA’ Flavors: r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64

Version: 2.0.8
Check: package dependencies
Result: NOTE Package suggested but not available for checking: 'RandomFields' Flavor: r-release-windows-x86_64