> library(rgdal)
Loading required package: sp
rgdal: version: 1.4-3, (SVN revision 828)
Geospatial Data Abstraction Library extensions to R successfully loaded
Loaded GDAL runtime: GDAL 2.2.3, released 2017/11/20
Path to GDAL shared files: /usr/share/gdal/2.2
GDAL binary built with GEOS: TRUE
Loaded PROJ.4 runtime: Rel. 4.9.3, 15 August 2016, [PJ_VERSION: 493]
Path to PROJ.4 shared files: (autodetected)
Linking to sp version: 1.3-1
> library(geoR)
'RandomFieldsUtils' will use OMP
'RandomFields' will use OMP
--------------------------------------------------------------
Analysis of Geostatistical Data
For an Introduction to geoR go to http://www.leg.ufpr.br/geoR
geoR version 1.7-5.2.1 (built on 2016-05-02) is now loaded
--------------------------------------------------------------
> library(plotKML)
plotKML version 0.5-9 (2019-01-04)
URL: http://plotkml.r-forge.r-project.org/
> library(raster)
> library(SuperLearner)
Loading required package: nnls
Super Learner
Version: 2.0-24
Package created on 2018-08-10
> library(subsemble)
subsemble (beta)
Version: 0.0.9.9000
Package created on 2014-12-09
Notice to subsemble users:
The interface (function arguments/values) may be subject to change prior to version 1.0.0.
> demo(meuse, echo=FALSE)
> m <- train.spLearner(meuse["lead"], covariates=meuse.grid[,c("dist","ffreq")], lambda = 1)
Error in train.spLearner(meuse["lead"], covariates = meuse.grid[, c("dist", :
could not find function "train.spLearner"
> library(landmap)
> demo(meuse, echo=FALSE)
> m <- train.spLearner(meuse["lead"], covariates=meuse.grid[,c("dist","ffreq")], lambda = 1)
Converting ffreq to indicators...
Converting covariates to principal components...
Deriving buffer distances to points...TRUE
Error in .solve.geoR(crossprod(xmat)) :
Singular matrix. Covariates may have different orders of magnitude.
In addition: Warning message:
In sqrt(t.ei$val) : NaNs produced
Fitting a variogram using 'linkfit' and trend model...TRUE
Error in c("practicalRange", "cov.model") %in% names(rvgm) :
object 'rvgm' not found
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and session info: