Last updated on 2025-02-16 08:51:39 CET.
| Package | ERROR | NOTE | OK |
|---|---|---|---|
| diseasemapping | 7 | 8 | |
| geostatsp | 1 | 8 | 6 |
| mapmisc | 15 | ||
| skellam | 5 | 10 |
Current CRAN status: NOTE: 7, OK: 8
Version: 2.0.6
Check: package dependencies
Result: NOTE
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
Current CRAN status: ERROR: 1, NOTE: 8, OK: 6
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’ [30m/16m]
Running ‘krige.R’ [13s/13s]
Running ‘lgcp.R’ [59s/38s]
Running ‘lgm.R’ [35s/32s]
Running ‘lgmRaster.R’ [31m/22m]
Running ‘likfitLgm.R’ [27s/31s]
Running ‘matern.R’ [15s/19s]
Running ‘maternGmrfPrec.R’ [36m/35m]
Running ‘profLlgm.R’ [0m/16m]
Running ‘simLgcp.R’
Running the tests in ‘tests/RFsimulate.R’ failed.
Complete output:
> library("geostatsp")
Loading required package: Matrix
Loading required package: terra
terra 1.8.21
>
> 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 1.8.21
> #'
>
> #' # 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 1.8.21
> 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
0.501 0.009 0.518
>
>
> system.time({theNNadj = NNmat(N=myr, nearest=params['shape']+1, adjustEdges=TRUE)})
user system elapsed
0.229 0.022 0.257
> # 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 1.8.21
> 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$logL
m2logL.ml logL.ml
644.4812 -322.2406
>
> date()
[1] "Wed Feb 12 17:31:46 2025"
> x=profLlgm(swissFit, mc.cores=Ncores,
+ range=seq(15000, 55000 , len=12)
+ )
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 2.0.8
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘RandomFields’
Package which this enhances but not available for checking: ‘INLA’
Flavors: r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 2.0.8
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: 'RandomFields'
Flavor: r-release-windows-x86_64
Version: 2.0.6
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘RandomFields’
Package which this enhances but not available for checking: ‘INLA’
Flavor: r-oldrel-macos-arm64
Current CRAN status: OK: 15
Current CRAN status: ERROR: 5, OK: 10
Version: 0.2.3
Check: examples
Result: ERROR
Running examples in ‘skellam-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: skellam.reg
> ### Title: Regression assuming a Skellam distribution
> ### Aliases: skellam.reg
> ### Keywords: Skellam regression
>
> ### ** Examples
>
> require('skellam')
>
> set.seed(0)
>
> x <- rnorm(1000)
> y1 <- rpois(1000, exp(1 + 1 * x) )
> y2 <- rpois(1000 , exp(-1 + 1 * x) )
> y <- y2 - y1
> skellam.reg(y, x)
Error in stats::optim(mod$estimate, skelreg, hessian = TRUE, control = list(maxit = 5000)) :
function cannot be evaluated at initial parameters
Calls: skellam.reg -> <Anonymous>
Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 0.2.3
Check: examples
Result: ERROR
Running examples in ‘skellam-Ex.R’ failed
The error most likely occurred in:
> ### Name: skellam.reg
> ### Title: Regression assuming a Skellam distribution
> ### Aliases: skellam.reg
> ### Keywords: Skellam regression
>
> ### ** Examples
>
> require('skellam')
>
> set.seed(0)
>
> x <- rnorm(1000)
> y1 <- rpois(1000, exp(1 + 1 * x) )
> y2 <- rpois(1000 , exp(-1 + 1 * x) )
> y <- y2 - y1
> skellam.reg(y, x)
Error in stats::optim(mod$estimate, skelreg, hessian = TRUE, control = list(maxit = 5000)) :
function cannot be evaluated at initial parameters
Calls: skellam.reg -> <Anonymous>
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.