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Updated: 9 min 5 sec ago

Re: CRAN releases of sp, rgdal and rgeos

Mon, 06/11/2018 - 02:53
On Mon, 11 Jun 2018, Gilles Benjamin Leduc wrote:

> Good monday!
>
> I tried to update rgdal, I get a warning telling me the installation had
> a non-null exit status. I haven't cheak if it was working…

Thanks for responding - every user data point helps!

Could you please provide the output of sessionInfo(), and any error
messages you see on trying to update?

Roger

>
> Benjamin
>
>
> Le Vendredi 8 Juin 2018 18:15 GMT, Roger Bivand <[hidden email]> a écrit:
>
>> There are new releases of sp, rgdal and rgeos on CRAN. Please install sp
>> first, then the other two, which link to the installed sp. They all
>
>> address so-called rchk issues, which have not so far been a problem, but
>> might have become more fragile as R's internal memory management is made
>> even more efficient. This involves compiled code using memory allocated by
>> R to be freed by R's garbage collector, which has to know if an object is
>> still being used. Tomas Kalibera, the author of rchk, helped resolve and
>> explain the issues encountered - what was good coding practice fifteen
>> years ago isn't always still good practice.
>>
>> In addition, the earliest versions of GDAL and PROJ with which rgdal will
>> work have been updated, and set to PROJ 4.8.0 and GDAL 1.11.4. The current
>> released versions of PROJ and GDAL are to be prefered, as bugs have been
>> fixed and new features and drivers introduced. A check has been put
>
>> in place to trap attempts to install rgdal without a C++11-capable
>> compiler when the GDAL version is >=2.3.0 - which requires C++11. rgeos is
>> ready for the forthcoming version of GEOS.
>>
>> The CRAN team has also been very supportive of our efforts to bring
>
>> compiled code in these packages into rchk compliance.
>>
>> Please get in touch if you see any loose ends in these releases.
>>
>> Roger
>>
>> --
>> Roger Bivand
>> Department of Economics, Norwegian School of Economics,
>> Helleveien 30, N-5045 Bergen, Norway.
>> voice: +47 55 95 93 55; e-mail: [hidden email]
>> http://orcid.org/0000-0003-2392-6140
>> https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
>>
>> _______________________________________________
>> R-sig-Geo mailing list
>> [hidden email]
>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>
>
>
>
> --
Roger Bivand
Department of Economics, Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; e-mail: [hidden email]
http://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
_______________________________________________
R-sig-Geo mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
Roger Bivand
Department of Economics
Norwegian School of Economics
Helleveien 30
N-5045 Bergen, Norway

Re: CRAN releases of sp, rgdal and rgeos

Mon, 06/11/2018 - 01:34
 Good monday!

I tried to update rgdal, I get a warning telling me the installation had a non-null exit status. I haven't cheak if it was working…

Benjamin
 
 
Le Vendredi 8 Juin 2018 18:15 GMT, Roger Bivand <[hidden email]> a écrit:
 
> There are new releases of sp, rgdal and rgeos on CRAN. Please install sp
> first, then the other two, which link to the installed sp. They all

> address so-called rchk issues, which have not so far been a problem, but
> might have become more fragile as R's internal memory management is made
> even more efficient. This involves compiled code using memory allocated by
> R to be freed by R's garbage collector, which has to know if an object is
> still being used. Tomas Kalibera, the author of rchk, helped resolve and
> explain the issues encountered - what was good coding practice fifteen
> years ago isn't always still good practice.
>
> In addition, the earliest versions of GDAL and PROJ with which rgdal will
> work have been updated, and set to PROJ 4.8.0 and GDAL 1.11.4. The current
> released versions of PROJ and GDAL are to be prefered, as bugs have been
> fixed and new features and drivers introduced. A check has been put
> in place to trap attempts to install rgdal without a C++11-capable
> compiler when the GDAL version is >=2.3.0 - which requires C++11. rgeos is
> ready for the forthcoming version of GEOS.
>
> The CRAN team has also been very supportive of our efforts to bring

> compiled code in these packages into rchk compliance.
>
> Please get in touch if you see any loose ends in these releases.
>
> Roger
>
> --
> Roger Bivand
> Department of Economics, Norwegian School of Economics,
> Helleveien 30, N-5045 Bergen, Norway.
> voice: +47 55 95 93 55; e-mail: [hidden email]
> http://orcid.org/0000-0003-2392-6140
> https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
>
> _______________________________________________
> R-sig-Geo mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
_______________________________________________
R-sig-Geo mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/r-sig-geo

Re: CRAN releases of sp, rgdal and rgeos

Sun, 06/10/2018 - 03:45
Thanks for reporting, comments inline below (note that I have no OSX
access at all):

On Sat, 9 Jun 2018, Thiago V. dos Santos wrote:

> Dear Roger,
> Thank you very much for the excellent work done with those packages.
> Today I update both rgeos and rgdal on my system - macOS 10.13.5 with
> all dependencies installed via MacPorts. I had updated sp a few days
> earlier. The dependencies versions on my system are gdal
> @2.3.0.20180523_0+grib+hdf4+hdf5+jasper+mpich+netcdf and proj @5.1.0_0.
> Rgeos's update went flawlessly, but I got a few errors while updating
> rgdal. It still compiled successfully, but I am concerned that some
> functionality might be compromised due to the errors.
> This is what I got (I have to manually specify the location of proj or
> rgdal won't find it):> install.packages('rgdal', type = "source",
> configure.args=c(
> +     '--with-proj-include=/opt/local/lib/proj5/include',
> +     '--with-proj-lib=/opt/local/lib/proj5/lib'))
> Installing package into ‘/Users/thiago/Documents/R-packages’
> (as ‘lib’ is unspecified)
> trying URL 'https://cran.r-project.org/src/contrib/rgdal_1.3-2.tar.gz'
> Content type 'application/x-gzip' length 1667049 bytes (1.6 MB)
> ==================================================
> downloaded 1.6 MB
>
> * installing *source* package ‘rgdal’ ...
> ** package ‘rgdal’ successfully unpacked and MD5 sums checked
> configure: CC: /usr/bin/clang
> configure: CXX: /usr/bin/clang++
> configure: rgdal: 1.3-2
> checking for /usr/bin/svnversion... yes
> configure: svn revision: 755
> checking whether the C++ compiler works... yes
> checking for C++ compiler default output file name... a.out
> checking for suffix of executables...
> checking whether we are cross compiling... no
> checking for suffix of object files... o
> checking whether we are using the GNU C++ compiler... yes
> checking whether /usr/bin/clang++ accepts -g... yes
> checking whether /usr/bin/clang++ supports C++11 features by default... no
> checking whether /usr/bin/clang++ supports C++11 features with -std=gnu++11... yes
> configure: C++11 support available
> checking for gdal-config... /opt/local/bin/gdal-config
> checking gdal-config usability... yes
> configure: GDAL: 2.4.0 All OK up to the GDAL version returned by gdal-config - are you using the
released GDAL 2.3.0 (probably not) or master?

> checking C++11 support for GDAL >= 2.3.0... yes
> checking GDAL version >= 1.11.4... yes
> checking gdal: linking with --libs only... yes
> checking GDAL: /opt/local/share/gdal/pcs.csv readable... yes
> checking proj_api.h presence and usability... yes
> ./configure: line 3395: test: =: unary operator expected

Will check, that line is:

if test ${PROJ_VERSION} = "" ; then

from configure.ac line 305. Possibly a shell dialect issue.

> checking PROJ version >= 4.8.0... yes
> checking projects.h presence and usability... yes

These relate to configure.ac lines 376-419, and the outcome: epsg found
and readable is OK - could there be two libproj on your system (maybe for
different architectures)?

> Undefined symbols for architecture x86_64:
>  "_pj_ctx_fclose", referenced from:
>      _main in proj_conf_test2-06fe7d.o
>  "_pj_get_default_ctx", referenced from:
>      _main in proj_conf_test2-06fe7d.o
>  "_pj_open_lib", referenced from:
>      _main in proj_conf_test2-06fe7d.o
> ld: symbol(s) not found for architecture x86_64
> clang: error: linker command failed with exit code 1 (use -v to see invocation)
> ./configure: line 3511: ./proj_conf_test2: No such file or directory
> checking PROJ.4: epsg found and readable... yes Same here for next block in configure.ac; conus found and readable.

> Undefined symbols for architecture x86_64:
>  "_pj_ctx_fclose", referenced from:
>      _main in proj_conf_test3-3b7aa2.o
>  "_pj_get_default_ctx", referenced from:
>      _main in proj_conf_test3-3b7aa2.o
>  "_pj_open_lib", referenced from:
>      _main in proj_conf_test3-3b7aa2.o
> ld: symbol(s) not found for architecture x86_64
> clang: error: linker command failed with exit code 1 (use -v to see invocation)
> ./configure: line 3570: ./proj_conf_test3: No such file or directory
> checking PROJ.4: conus found and readable... yes
> configure: Package CPP flags:  -I/opt/local/include -I/opt/local/lib/proj5/include
> configure: Package LIBS:  -L/opt/local/lib -lgdal -L/opt/local/lib/proj5/lib -lproj
> configure: creating ./config.status
> config.status: creating src/Makevars
> ** libs
> clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c OGR_write.cpp -o OGR_write.o
> clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c gdal-bindings.cpp -o gdal-bindings.o
> /usr/bin/clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c init.c -o init.o
> /usr/bin/clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c inverser.c -o inverser.o
> /usr/bin/clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c local_stubs.c -o local_stubs.o
> clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c ogr_geom.cpp -o ogr_geom.o
> /usr/bin/clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c ogr_polygons.c -o ogr_polygons.o
> clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c ogr_proj.cpp -o ogr_proj.o
> clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c ogrdrivers.cpp -o ogrdrivers.o
> clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c ogrsource.cpp -o ogrsource.o
> clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c projectit.cpp -o projectit.o
> clang++ -std=gnu++11 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -single_module -multiply_defined suppress -L/Library/Frameworks/R.framework/Resources/lib -L/usr/local/lib -o rgdal.so OGR_write.o gdal-bindings.o init.o inverser.o local_stubs.o ogr_geom.o ogr_polygons.o ogr_proj.o ogrdrivers.o ogrsource.o projectit.o -L/opt/local/lib -lgdal -L/opt/local/lib/proj5/lib -lproj -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
> installing to /Users/thiago/Documents/R-packages/rgdal/libs
> ** R
> ** data
> ** inst
> ** byte-compile and prepare package for lazy loading
> ** help
> *** installing help indices
> ** building package indices
> ** installing vignettes
> ** testing if installed package can be loaded
> * DONE (rgdal)
>
> The downloaded source packages are in
>
> ‘/private/var/folders/_z/01gg71zs19g816v6m2dddt8w0000gn/T/Rtmp5K6lt8/downloaded_packages’
> ​Is this something that needs to be investigated, or I can just safely
> ignore those messages? Please try to run:

tools::testInstalledPackage("rgdal", outDir=tempdir())
list.files(tempdir())
file.show(file.path(tempdir(), "rgdal-Ex.Rout"))

and if the outcomes are as expected, you should be OK, please let us know.

If any OSX users installing from source can contribute, that would be
useful. It will take a little while before the CRAN OSX binaries catch up
with new PROJ and GDAL.

Again thanks for reporting!

Roger

> Many thanks, -- Thiago V. dos Santos
> Postdoctoral Research FellowDepartment of Climate and Space Science and EngineeringUniversity of Michigan
>
>    On Friday, June 8, 2018, 2:15:43 PM EDT, Roger Bivand <[hidden email]> wrote:
>
> There are new releases of sp, rgdal and rgeos on CRAN. Please install sp
> first, then the other two, which link to the installed sp. They all
> address so-called rchk issues, which have not so far been a problem, but
> might have become more fragile as R's internal memory management is made
> even more efficient. This involves compiled code using memory allocated by
> R to be freed by R's garbage collector, which has to know if an object is
> still being used. Tomas Kalibera, the author of rchk, helped resolve and
> explain the issues encountered - what was good coding practice fifteen
> years ago isn't always still good practice.
>
> In addition, the earliest versions of GDAL and PROJ with which rgdal will
> work have been updated, and set to PROJ 4.8.0 and GDAL 1.11.4. The current
> released versions of PROJ and GDAL are to be prefered, as bugs have been
> fixed and new features and drivers introduced. A check has been put
> in place to trap attempts to install rgdal without a C++11-capable
> compiler when the GDAL version is >=2.3.0 - which requires C++11. rgeos is
> ready for the forthcoming version of GEOS.
>
> The CRAN team has also been very supportive of our efforts to bring
> compiled code in these packages into rchk compliance.
>
> Please get in touch if you see any loose ends in these releases.
>
> Roger
>
> --
Roger Bivand
Department of Economics, Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; e-mail: [hidden email]
http://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
_______________________________________________
R-sig-Geo mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
Roger Bivand
Department of Economics
Norwegian School of Economics
Helleveien 30
N-5045 Bergen, Norway

Re: CRAN releases of sp, rgdal and rgeos

Sat, 06/09/2018 - 14:46
Dear Roger,
Thank you very much for the excellent work done with those packages.
Today I update both rgeos and rgdal on my system - macOS 10.13.5 with all dependencies installed via MacPorts. I had updated sp a few days earlier.
The dependencies versions on my system are gdal @2.3.0.20180523_0+grib+hdf4+hdf5+jasper+mpich+netcdf and proj @5.1.0_0.
Rgeos's update went flawlessly, but I got a few errors while updating rgdal. It still compiled successfully, but I am concerned that some functionality might be compromised due to the errors.
This is what I got (I have to manually specify the location of proj or rgdal won't find it):> install.packages('rgdal', type = "source", configure.args=c(
+     '--with-proj-include=/opt/local/lib/proj5/include',
+     '--with-proj-lib=/opt/local/lib/proj5/lib'))
Installing package into ‘/Users/thiago/Documents/R-packages’
(as ‘lib’ is unspecified)
trying URL 'https://cran.r-project.org/src/contrib/rgdal_1.3-2.tar.gz'
Content type 'application/x-gzip' length 1667049 bytes (1.6 MB)
==================================================
downloaded 1.6 MB

* installing *source* package ‘rgdal’ ...
** package ‘rgdal’ successfully unpacked and MD5 sums checked
configure: CC: /usr/bin/clang
configure: CXX: /usr/bin/clang++
configure: rgdal: 1.3-2
checking for /usr/bin/svnversion... yes
configure: svn revision: 755
checking whether the C++ compiler works... yes
checking for C++ compiler default output file name... a.out
checking for suffix of executables...
checking whether we are cross compiling... no
checking for suffix of object files... o
checking whether we are using the GNU C++ compiler... yes
checking whether /usr/bin/clang++ accepts -g... yes
checking whether /usr/bin/clang++ supports C++11 features by default... no
checking whether /usr/bin/clang++ supports C++11 features with -std=gnu++11... yes
configure: C++11 support available
checking for gdal-config... /opt/local/bin/gdal-config
checking gdal-config usability... yes
configure: GDAL: 2.4.0
checking C++11 support for GDAL >= 2.3.0... yes
checking GDAL version >= 1.11.4... yes
checking gdal: linking with --libs only... yes
checking GDAL: /opt/local/share/gdal/pcs.csv readable... yes
checking proj_api.h presence and usability... yes
./configure: line 3395: test: =: unary operator expected
checking PROJ version >= 4.8.0... yes
checking projects.h presence and usability... yes
Undefined symbols for architecture x86_64:
  "_pj_ctx_fclose", referenced from:
      _main in proj_conf_test2-06fe7d.o
  "_pj_get_default_ctx", referenced from:
      _main in proj_conf_test2-06fe7d.o
  "_pj_open_lib", referenced from:
      _main in proj_conf_test2-06fe7d.o
ld: symbol(s) not found for architecture x86_64
clang: error: linker command failed with exit code 1 (use -v to see invocation)
./configure: line 3511: ./proj_conf_test2: No such file or directory
checking PROJ.4: epsg found and readable... yes
Undefined symbols for architecture x86_64:
  "_pj_ctx_fclose", referenced from:
      _main in proj_conf_test3-3b7aa2.o
  "_pj_get_default_ctx", referenced from:
      _main in proj_conf_test3-3b7aa2.o
  "_pj_open_lib", referenced from:
      _main in proj_conf_test3-3b7aa2.o
ld: symbol(s) not found for architecture x86_64
clang: error: linker command failed with exit code 1 (use -v to see invocation)
./configure: line 3570: ./proj_conf_test3: No such file or directory
checking PROJ.4: conus found and readable... yes
configure: Package CPP flags:  -I/opt/local/include -I/opt/local/lib/proj5/include
configure: Package LIBS:  -L/opt/local/lib -lgdal -L/opt/local/lib/proj5/lib -lproj
configure: creating ./config.status
config.status: creating src/Makevars
** libs
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c OGR_write.cpp -o OGR_write.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c gdal-bindings.cpp -o gdal-bindings.o
/usr/bin/clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c init.c -o init.o
/usr/bin/clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c inverser.c -o inverser.o
/usr/bin/clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c local_stubs.c -o local_stubs.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c ogr_geom.cpp -o ogr_geom.o
/usr/bin/clang -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c ogr_polygons.c -o ogr_polygons.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c ogr_proj.cpp -o ogr_proj.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c ogrdrivers.cpp -o ogrdrivers.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c ogrsource.cpp -o ogrsource.o
clang++ -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/local/include -I/opt/local/lib/proj5/include -I"/Users/thiago/Documents/R-packages/sp/include" -I/usr/local/include   -fPIC  -Wall -g -O2 -c projectit.cpp -o projectit.o
clang++ -std=gnu++11 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -single_module -multiply_defined suppress -L/Library/Frameworks/R.framework/Resources/lib -L/usr/local/lib -o rgdal.so OGR_write.o gdal-bindings.o init.o inverser.o local_stubs.o ogr_geom.o ogr_polygons.o ogr_proj.o ogrdrivers.o ogrsource.o projectit.o -L/opt/local/lib -lgdal -L/opt/local/lib/proj5/lib -lproj -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Users/thiago/Documents/R-packages/rgdal/libs
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (rgdal)

The downloaded source packages are in
    ‘/private/var/folders/_z/01gg71zs19g816v6m2dddt8w0000gn/T/Rtmp5K6lt8/downloaded_packages’

Is this something that needs to be investigated, or I can just safely ignore those messages?
Many thanks, -- Thiago V. dos Santos
Postdoctoral Research FellowDepartment of Climate and Space Science and EngineeringUniversity of Michigan

    On Friday, June 8, 2018, 2:15:43 PM EDT, Roger Bivand <[hidden email]> wrote:  
 
 There are new releases of sp, rgdal and rgeos on CRAN. Please install sp
first, then the other two, which link to the installed sp. They all
address so-called rchk issues, which have not so far been a problem, but
might have become more fragile as R's internal memory management is made
even more efficient. This involves compiled code using memory allocated by
R to be freed by R's garbage collector, which has to know if an object is
still being used. Tomas Kalibera, the author of rchk, helped resolve and
explain the issues encountered - what was good coding practice fifteen
years ago isn't always still good practice.

In addition, the earliest versions of GDAL and PROJ with which rgdal will
work have been updated, and set to PROJ 4.8.0 and GDAL 1.11.4. The current
released versions of PROJ and GDAL are to be prefered, as bugs have been
fixed and new features and drivers introduced. A check has been put
in place to trap attempts to install rgdal without a C++11-capable
compiler when the GDAL version is >=2.3.0 - which requires C++11. rgeos is
ready for the forthcoming version of GEOS.

The CRAN team has also been very supportive of our efforts to bring
compiled code in these packages into rchk compliance.

Please get in touch if you see any loose ends in these releases.

Roger

--
Roger Bivand
Department of Economics, Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; e-mail: [hidden email]
http://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en

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Re: CRAN releases of sp, rgdal and rgeos

Sat, 06/09/2018 - 01:56
sp 1.3-1, rgdal 1.3-2, rgeos 0.3-28.

Roger Bivand
Norwegian School of Economics
Bergen, Norway



Fra: Greg Minshall
Sendt: lørdag 9. juni, 01.33
Emne: Re: [R-sig-Geo] CRAN releases of sp, rgdal and rgeos
Til: Roger Bivand
Kopi: [hidden email]


hi, Roger, could you give the version numbers of the new sp, rgdal, rgeos? (not that i don't trust CRAN to be up-to-date.) cheers, Greg


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Norwegian School of Economics
Helleveien 30
N-5045 Bergen, Norway

Re: CRAN releases of sp, rgdal and rgeos

Fri, 06/08/2018 - 18:33
hi, Roger,

could you give the version numbers of the new sp, rgdal, rgeos?  (not
that i don't trust CRAN to be up-to-date.)

cheers, Greg

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CRAN releases of sp, rgdal and rgeos

Fri, 06/08/2018 - 13:15
There are new releases of sp, rgdal and rgeos on CRAN. Please install sp
first, then the other two, which link to the installed sp. They all
address so-called rchk issues, which have not so far been a problem, but
might have become more fragile as R's internal memory management is made
even more efficient. This involves compiled code using memory allocated by
R to be freed by R's garbage collector, which has to know if an object is
still being used. Tomas Kalibera, the author of rchk, helped resolve and
explain the issues encountered - what was good coding practice fifteen
years ago isn't always still good practice.

In addition, the earliest versions of GDAL and PROJ with which rgdal will
work have been updated, and set to PROJ 4.8.0 and GDAL 1.11.4. The current
released versions of PROJ and GDAL are to be prefered, as bugs have been
fixed and new features and drivers introduced. A check has been put
in place to trap attempts to install rgdal without a C++11-capable
compiler when the GDAL version is >=2.3.0 - which requires C++11. rgeos is
ready for the forthcoming version of GEOS.

The CRAN team has also been very supportive of our efforts to bring
compiled code in these packages into rchk compliance.

Please get in touch if you see any loose ends in these releases.

Roger

--
Roger Bivand
Department of Economics, Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; e-mail: [hidden email]
http://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en

_______________________________________________
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Roger Bivand
Department of Economics
Norwegian School of Economics
Helleveien 30
N-5045 Bergen, Norway

Re: Spatiotemporal autocorrelation in R

Fri, 06/08/2018 - 08:01
There are a couple software packages you might want to check out.  I believe Geoda (Luc Anselin) has bivariate LISA functions and LISTA-Viz has spatiotemporal autocorrelation functions as well.



Nathen M. Harp
Transportation - GIS Analyst
NYSDOT-Policy & Planning Division
Demographic Analysis & Forecasting
Fl 6 - Ave E - 10th St
50 Wolf Rd.
Albany, NY 12232
Ph: 518-485-0968
Fx: 518-485-8276
Email: [hidden email]


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Re: Spatiotemporal autocorrelation in R

Thu, 06/07/2018 - 16:17
Hi Laura,

I don't know any specific function/package that does precisely what you
want to do. A while ago, I wanted to run a bivariate spatial correlation in
R (bivariate LISA) and I couldn't find package with a function for such
task, despite being a fairly simple task. In the end, a colleague of mine
developed such function and we shared on StackOverflow and here in this
group as well. Link to SO:
https://stackoverflow.com/questions/45177590/map-of-bivariate-spatial-correlation-in-r-bivariate-lisa

Perhaps Chenhua Shen would be willing to share their code.

best,

Rafael H.M. Pereira
Transport Studies Unit (TSU)
Oxford University

On Thu, Jun 7, 2018 at 5:15 PM, Todd McDonnell <
[hidden email]> wrote:

> The ccf can be used to compare two time-series that occur at the same
> location or at different locations. You could loop through all possible
> pairs of time-series at the same or different locations to determine which
> were more or less correlated. I am not sure how to do the spatial and the
> temporal correlations simultaneously.
>
> Todd
>
> On June 7, 2018 12:13:01 PM MST, Laura Cabral <[hidden email]> wrote:
> >Hi Todd,
> >
> >Thank you for your suggestion. As I understand it, this takes care of
> >the temporal aspect, but not the spatial aspect, am I right?
> >
> >Thank you,
> >Laura Cabral
> >
> >
> >
> >MSc Candidate in Transportation Engineering
> >
> >Dept of Civil and Environmental Engineering
> >
> >University of Alberta
> >
> >[hidden email] <mailto:[hidden email]>
> >819 993-1901
> >
> >
> >The University of Alberta is located in ᐊᒥᐢᑿᒌᐚᐢᑲᐦᐃᑲᐣ
> >(Amiskwacîwâskahikan) on Treaty 6 territory, homeland of the Papaschase
> >and the Métis Nation
> >
> >> Le 7 juin 2018 à 12:42, Todd McDonnell
> ><[hidden email]> a écrit :
> >>
> >> Hi Laura,
> >>
> >> It sounds like you may want to explore using the cross-correlation
> >function (ccf) to compare the two sets of data through time:
> >> http://stat.ethz.ch/R-manual/R-devel/library/stats/html/acf.html
> >>
> >> Todd
> >>
> >> --
> >> Todd McDonnell
> >> Research Scientist, Ph.D.
> >> E&S Environmental Chemistry
> >> Corvallis, OR | Ph. 541-758-1330
> >> www.esenvironmental.com
> >>
> >> -----Original Message-----
> >> From: R-sig-Geo [mailto:[hidden email]] On Behalf Of
> >Laura Cabral
> >> Sent: Thursday, June 07, 2018 11:03 AM
> >> To: [hidden email]
> >> Subject: [R-sig-Geo] Spatiotemporal autocorrelation in R
> >>
> >> Hello All,
> >>
> >> I have been reading about spatiotemporal autocorrelation and slowly
> >familiarizing myself with the concepts involved. I have also been
> >combing through the CRAN spatiotemporal task view, but I can’t seem to
> >find the appropriate package/function for my purposes.
> >>
> >> What I want to do:
> >> I have two series of count data each for the same times and
> >locations. Both series have been ordered from lowest count to highest
> >count. I would like to identify where/when in space-time the series are
> >similar (low-low count clusters, high-high count clusters) and where
> >they do not correspond (high-low or low-high). Really, I am looking for
> >a Moran’s I type index which can handle spatiotemporal data. I know
> >this type of index has been developed (see for example Shen, Li and Si,
> >2016 - Spatiotemporal autocorrelation measures for nonstationary
> >series), but I am unsure whether any of it has been translated into an
> >R package/function. I do not (yet) have the
> >mathematical/statistical/programming knowledge to implement those
> >myself.
> >>
> >>
> >> What I don’t want to do:
> >> I have seen quite a bit of discussions or packages aimed at
> >detrending or modelling the data. I do not need these functionalities.
> >I have also seen separate handling of spatial and temporal
> >autocorrelation for the same dataset. I would prefer an integrated
> >index, if that is possible.
> >>
> >> I feel like I might be looking for the wrong keywords, so any
> >keywords, packages, functions, tutorials, videos, etc. that you could
> >recommend would be greatly beneficial. As I mentioned, I am still
> >familiarizing myself with spatiotemporal autocorrelation concepts, so
> >if I seem to be approaching this from the completely wrong angle,
> >please let me know!
> >>
> >> Thank you all for your help,
> >>
> >> Laura Cabral
> >>
> >>
> >>
> >> MSc Candidate in Transportation Engineering
> >>
> >> Dept of Civil and Environmental Engineering
> >>
> >> University of Alberta
> >>
> >> [hidden email] <mailto:[hidden email]>
> >> 819 993-1901
> >>
> >>
> >> The University of Alberta is located in ᐊᒥᐢᑿᒌᐚᐢᑲᐦᐃᑲᐣ
> >(Amiskwacîwâskahikan) on Treaty 6 territory, homeland of the Papaschase
> >and the Métis Nation
> >>
> >>
> >>      [[alternative HTML version deleted]]
> >>
> >> _______________________________________________
> >> R-sig-Geo mailing list
> >> [hidden email]
> >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >>
>
>         [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-Geo mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>
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Re: Spatiotemporal autocorrelation in R

Thu, 06/07/2018 - 15:15
The ccf can be used to compare two time-series that occur at the same location or at different locations. You could loop through all possible pairs of time-series at the same or different locations to determine which were more or less correlated. I am not sure how to do the spatial and the temporal correlations simultaneously.

Todd

On June 7, 2018 12:13:01 PM MST, Laura Cabral <[hidden email]> wrote:
>Hi Todd,
>
>Thank you for your suggestion. As I understand it, this takes care of
>the temporal aspect, but not the spatial aspect, am I right?
>
>Thank you,
>Laura Cabral
>
>
>
>MSc Candidate in Transportation Engineering
>
>Dept of Civil and Environmental Engineering
>
>University of Alberta
>
>[hidden email] <mailto:[hidden email]>
>819 993-1901
>
>
>The University of Alberta is located in ᐊᒥᐢᑿᒌᐚᐢᑲᐦᐃᑲᐣ
>(Amiskwacîwâskahikan) on Treaty 6 territory, homeland of the Papaschase
>and the Métis Nation
>
>> Le 7 juin 2018 à 12:42, Todd McDonnell
><[hidden email]> a écrit :
>>
>> Hi Laura,
>>
>> It sounds like you may want to explore using the cross-correlation
>function (ccf) to compare the two sets of data through time:
>> http://stat.ethz.ch/R-manual/R-devel/library/stats/html/acf.html
>>
>> Todd
>>
>> --
>> Todd McDonnell
>> Research Scientist, Ph.D.
>> E&S Environmental Chemistry
>> Corvallis, OR | Ph. 541-758-1330
>> www.esenvironmental.com
>>
>> -----Original Message-----
>> From: R-sig-Geo [mailto:[hidden email]] On Behalf Of
>Laura Cabral
>> Sent: Thursday, June 07, 2018 11:03 AM
>> To: [hidden email]
>> Subject: [R-sig-Geo] Spatiotemporal autocorrelation in R
>>
>> Hello All,
>>
>> I have been reading about spatiotemporal autocorrelation and slowly
>familiarizing myself with the concepts involved. I have also been
>combing through the CRAN spatiotemporal task view, but I can’t seem to
>find the appropriate package/function for my purposes.
>>
>> What I want to do:
>> I have two series of count data each for the same times and
>locations. Both series have been ordered from lowest count to highest
>count. I would like to identify where/when in space-time the series are
>similar (low-low count clusters, high-high count clusters) and where
>they do not correspond (high-low or low-high). Really, I am looking for
>a Moran’s I type index which can handle spatiotemporal data. I know
>this type of index has been developed (see for example Shen, Li and Si,
>2016 - Spatiotemporal autocorrelation measures for nonstationary
>series), but I am unsure whether any of it has been translated into an
>R package/function. I do not (yet) have the
>mathematical/statistical/programming knowledge to implement those
>myself.
>>
>>
>> What I don’t want to do:
>> I have seen quite a bit of discussions or packages aimed at
>detrending or modelling the data. I do not need these functionalities.
>I have also seen separate handling of spatial and temporal
>autocorrelation for the same dataset. I would prefer an integrated
>index, if that is possible.
>>
>> I feel like I might be looking for the wrong keywords, so any
>keywords, packages, functions, tutorials, videos, etc. that you could
>recommend would be greatly beneficial. As I mentioned, I am still
>familiarizing myself with spatiotemporal autocorrelation concepts, so
>if I seem to be approaching this from the completely wrong angle,
>please let me know!
>>
>> Thank you all for your help,
>>
>> Laura Cabral
>>
>>
>>
>> MSc Candidate in Transportation Engineering
>>
>> Dept of Civil and Environmental Engineering
>>
>> University of Alberta
>>
>> [hidden email] <mailto:[hidden email]>
>> 819 993-1901
>>
>>
>> The University of Alberta is located in ᐊᒥᐢᑿᒌᐚᐢᑲᐦᐃᑲᐣ
>(Amiskwacîwâskahikan) on Treaty 6 territory, homeland of the Papaschase
>and the Métis Nation
>>
>>
>> [[alternative HTML version deleted]]
>>
>> _______________________________________________
>> R-sig-Geo mailing list
>> [hidden email]
>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>
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Re: Spatiotemporal autocorrelation in R

Thu, 06/07/2018 - 14:13
Hi Todd,

Thank you for your suggestion. As I understand it, this takes care of the temporal aspect, but not the spatial aspect, am I right?

Thank you,
Laura Cabral

 

MSc Candidate in Transportation Engineering

Dept of Civil and Environmental Engineering

University of Alberta

[hidden email] <mailto:[hidden email]>
819 993-1901


The University of Alberta is located in ᐊᒥᐢᑿᒌᐚᐢᑲᐦᐃᑲᐣ (Amiskwacîwâskahikan) on Treaty 6 territory, homeland of the Papaschase and the Métis Nation

> Le 7 juin 2018 à 12:42, Todd McDonnell <[hidden email]> a écrit :
>
> Hi Laura,
>
> It sounds like you may want to explore using the cross-correlation function (ccf) to compare the two sets of data through time:
> http://stat.ethz.ch/R-manual/R-devel/library/stats/html/acf.html
>
> Todd
>
> --
> Todd McDonnell
> Research Scientist, Ph.D.
> E&S Environmental Chemistry
> Corvallis, OR | Ph. 541-758-1330
> www.esenvironmental.com
>
> -----Original Message-----
> From: R-sig-Geo [mailto:[hidden email]] On Behalf Of Laura Cabral
> Sent: Thursday, June 07, 2018 11:03 AM
> To: [hidden email]
> Subject: [R-sig-Geo] Spatiotemporal autocorrelation in R
>
> Hello All,
>
> I have been reading about spatiotemporal autocorrelation and slowly familiarizing myself with the concepts involved. I have also been combing through the CRAN spatiotemporal task view, but I can’t seem to find the appropriate package/function for my purposes.
>
> What I want to do:
> I have two series of count data each for the same times and locations. Both series have been ordered from lowest count to highest count. I would like to identify where/when in space-time the series are similar (low-low count clusters, high-high count clusters) and where they do not correspond (high-low or low-high). Really, I am looking for a Moran’s I type index which can handle spatiotemporal data. I know this type of index has been developed (see for example Shen, Li and Si, 2016 - Spatiotemporal autocorrelation measures for nonstationary series), but I am unsure whether any of it has been translated into an R package/function. I do not (yet) have the mathematical/statistical/programming knowledge to implement those myself.
>
>
> What I don’t want to do:
> I have seen quite a bit of discussions or packages aimed at detrending or modelling the data. I do not need these functionalities. I have also seen separate handling of spatial and temporal autocorrelation for the same dataset. I would prefer an integrated index, if that is possible.
>
> I feel like I might be looking for the wrong keywords, so any keywords, packages, functions, tutorials, videos, etc. that you could recommend would be greatly beneficial. As I mentioned, I am still familiarizing myself with spatiotemporal autocorrelation concepts, so if I seem to be approaching this from the completely wrong angle, please let me know!
>
> Thank you all for your help,
>
> Laura Cabral
>
>
>
> MSc Candidate in Transportation Engineering
>
> Dept of Civil and Environmental Engineering
>
> University of Alberta
>
> [hidden email] <mailto:[hidden email]>
> 819 993-1901
>
>
> The University of Alberta is located in ᐊᒥᐢᑿᒌᐚᐢᑲᐦᐃᑲᐣ (Amiskwacîwâskahikan) on Treaty 6 territory, homeland of the Papaschase and the Métis Nation
>
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-Geo mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>

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Re: Spatiotemporal autocorrelation in R

Thu, 06/07/2018 - 13:42
Hi Laura,

It sounds like you may want to explore using the cross-correlation function (ccf) to compare the two sets of data through time:
http://stat.ethz.ch/R-manual/R-devel/library/stats/html/acf.html

Todd

--
Todd McDonnell
Research Scientist, Ph.D.
E&S Environmental Chemistry
Corvallis, OR | Ph. 541-758-1330
www.esenvironmental.com

-----Original Message-----
From: R-sig-Geo [mailto:[hidden email]] On Behalf Of Laura Cabral
Sent: Thursday, June 07, 2018 11:03 AM
To: [hidden email]
Subject: [R-sig-Geo] Spatiotemporal autocorrelation in R

Hello All,

I have been reading about spatiotemporal autocorrelation and slowly familiarizing myself with the concepts involved. I have also been combing through the CRAN spatiotemporal task view, but I can’t seem to find the appropriate package/function for my purposes.

What I want to do:
I have two series of count data each for the same times and locations. Both series have been ordered from lowest count to highest count. I would like to identify where/when in space-time the series are similar (low-low count clusters, high-high count clusters) and where they do not correspond (high-low or low-high). Really, I am looking for a Moran’s I type index which can handle spatiotemporal data. I know this type of index has been developed (see for example Shen, Li and Si, 2016 - Spatiotemporal autocorrelation measures for nonstationary series), but I am unsure whether any of it has been translated into an R package/function. I do not (yet) have the mathematical/statistical/programming knowledge to implement those myself.


What I don’t want to do:
I have seen quite a bit of discussions or packages aimed at detrending or modelling the data. I do not need these functionalities. I have also seen separate handling of spatial and temporal autocorrelation for the same dataset. I would prefer an integrated index, if that is possible.

I feel like I might be looking for the wrong keywords, so any keywords, packages, functions, tutorials, videos, etc. that you could recommend would be greatly beneficial. As I mentioned, I am still familiarizing myself with spatiotemporal autocorrelation concepts, so if I seem to be approaching this from the completely wrong angle, please let me know!

Thank you all for your help,

Laura Cabral

 

MSc Candidate in Transportation Engineering

Dept of Civil and Environmental Engineering

University of Alberta

[hidden email] <mailto:[hidden email]>
819 993-1901


The University of Alberta is located in ᐊᒥᐢᑿᒌᐚᐢᑲᐦᐃᑲᐣ (Amiskwacîwâskahikan) on Treaty 6 territory, homeland of the Papaschase and the Métis Nation


        [[alternative HTML version deleted]]

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Spatiotemporal autocorrelation in R

Thu, 06/07/2018 - 13:02
Hello All,

I have been reading about spatiotemporal autocorrelation and slowly familiarizing myself with the concepts involved. I have also been combing through the CRAN spatiotemporal task view, but I can’t seem to find the appropriate package/function for my purposes.

What I want to do:
I have two series of count data each for the same times and locations. Both series have been ordered from lowest count to highest count. I would like to identify where/when in space-time the series are similar (low-low count clusters, high-high count clusters) and where they do not correspond (high-low or low-high). Really, I am looking for a Moran’s I type index which can handle spatiotemporal data. I know this type of index has been developed (see for example Shen, Li and Si, 2016 - Spatiotemporal autocorrelation measures for nonstationary series), but I am unsure whether any of it has been translated into an R package/function. I do not (yet) have the mathematical/statistical/programming knowledge to implement those myself.


What I don’t want to do:
I have seen quite a bit of discussions or packages aimed at detrending or modelling the data. I do not need these functionalities. I have also seen separate handling of spatial and temporal autocorrelation for the same dataset. I would prefer an integrated index, if that is possible.

I feel like I might be looking for the wrong keywords, so any keywords, packages, functions, tutorials, videos, etc. that you could recommend would be greatly beneficial. As I mentioned, I am still familiarizing myself with spatiotemporal autocorrelation concepts, so if I seem to be approaching this from the completely wrong angle, please let me know!

Thank you all for your help,

Laura Cabral

 

MSc Candidate in Transportation Engineering

Dept of Civil and Environmental Engineering

University of Alberta

[hidden email] <mailto:[hidden email]>
819 993-1901


The University of Alberta is located in ᐊᒥᐢᑿᒌᐚᐢᑲᐦᐃᑲᐣ (Amiskwacîwâskahikan) on Treaty 6 territory, homeland of the Papaschase and the Métis Nation


        [[alternative HTML version deleted]]

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Re: regression with Moran eigenvectors for multiple

Wed, 06/06/2018 - 12:02
Many thanks Roberto for these very helpful references and R code.
They are just what I am looking for and much appreciated. It is interesting
that such approaches don't seem very common.

Thank you again,
Thomas

On Tue, Jun 5, 2018 at 9:57 AM, Roberto Patuelli <[hidden email]>
wrote:

> Dear Thomas,
>
> I've worked with Moran eigenvectors.
> In some previous papers, I've used panel data with it.
>
> In this article
>
> Patuelli, R., D.A. Griffith, M. Tiefelsdorf and P. Nijkamp (2011). Spatial
> Filtering and Eigenvector Stability: Space-Time Models for German
> Unemployment Data. International Regional Science Review 34 (2): 253-80.
> R code: https://sites.google.com/Desktop/RPDGMTPN2011IRSR_(R_code).zip.
>
> I obtained a filter for each year and examined common eigenvectors.
>
> In this further article
>
> Patuelli, R., N. Schanne, D.A. Griffith and P. Nijkamp (2012). Persistence
> of Regional Unemployment: Application of a Spatial Filtering Approach to
> Local Labor Markets in Germany. Journal of Regional Science 52 (2): 300-23.
>
> I instead estimated dynamic panels (LSDV) using spatial filters as
> substitutes of fixed effects (in addition to using them for heterogeneous
> coefficients). I can provide you with me code for this article too, if you
> want.
>
> Best regards,
> Roberto Patuelli
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Mon, 4 Jun 2018 06:12:00 -0700
> From: Thomas Young <[hidden email]>
> To: [hidden email]
> Subject: [R-sig-Geo] regression with Moran eigenvectors for multiple
>         years of data
> Message-ID:
>         <CAMJGZtxbhE7ES8XPBgxqGmLsu0q--iid+nB1ysa8BG2fd4RpVA@mail.
> gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Hello,
>
> I think this is mostly a statistics question with possibly some R details.
> Any feedback is appreciated.
>
> I have several years of spatial biological sampling data in the same
> region but the number and locations of sites vary across year.  Very strong
> spatial autocorrelation is present in the data.
>
> I want to construct a regression model using Moran' eigenvectors as
> explanatory variables to account for SAC. For example,
>
> y_ijk=intercept+x1_ijk+x2_ijk+ EV_k
>
> where x1,x2 are environmental covariates and EV are Moran eigenvectors;
> i,j are location and k is year.
> Environmental covariate relationships with response variable are assumed
> constant across years.
>
> My plan was to first estimate using all years of data:
> y=intercept+x1+x2
> then use function ME in spdep to find identify Moran eigenvectors to
> reduce residual SAC using a year specific (index k) spatial weights and
> year-specific residuals using function ME from spdep package:
> EV_k=  ME(residuals_k~1, listw=weights_k), then linearly combine resulting
> eigenvectors for a given year into a single vector and then concatenate
> each year's vector such that the final Moran eignevector used in the
> regression is EV= c(EV_2014,EV_2015,EV_2016)
>
> and add EV as an offset or covariate as in the first equation shown.
>
> This approach seems to work quite well (eliminates residual SAC, doesn't
> shift regression coefficients substantially, improves model fit), I just
> don't know if it is statistically sound?
>
> thanks!
>
>         [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-Geo mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>
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Re: regression with Moran eigenvectors for multiple

Tue, 06/05/2018 - 11:57
Dear Thomas,

I've worked with Moran eigenvectors.
In some previous papers, I've used panel data with it.

In this article

Patuelli, R., D.A. Griffith, M. Tiefelsdorf and P. Nijkamp (2011). Spatial Filtering and Eigenvector Stability: Space-Time Models for German Unemployment Data. International Regional Science Review 34 (2): 253-80.
R code: https://sites.google.com/Desktop/RPDGMTPN2011IRSR_(R_code).zip.

I obtained a filter for each year and examined common eigenvectors.

In this further article

Patuelli, R., N. Schanne, D.A. Griffith and P. Nijkamp (2012). Persistence of Regional Unemployment: Application of a Spatial Filtering Approach to Local Labor Markets in Germany. Journal of Regional Science 52 (2): 300-23.

I instead estimated dynamic panels (LSDV) using spatial filters as substitutes of fixed effects (in addition to using them for heterogeneous coefficients). I can provide you with me code for this article too, if you want.

Best regards,
Roberto Patuelli

----------------------------------------------------------------------

Message: 1
Date: Mon, 4 Jun 2018 06:12:00 -0700
From: Thomas Young <[hidden email]>
To: [hidden email]
Subject: [R-sig-Geo] regression with Moran eigenvectors for multiple
        years of data
Message-ID:
        <[hidden email]>
Content-Type: text/plain; charset="utf-8"

Hello,

I think this is mostly a statistics question with possibly some R details.
Any feedback is appreciated.

I have several years of spatial biological sampling data in the same region but the number and locations of sites vary across year.  Very strong spatial autocorrelation is present in the data.

I want to construct a regression model using Moran' eigenvectors as explanatory variables to account for SAC. For example,

y_ijk=intercept+x1_ijk+x2_ijk+ EV_k

where x1,x2 are environmental covariates and EV are Moran eigenvectors; i,j are location and k is year.
Environmental covariate relationships with response variable are assumed constant across years.

My plan was to first estimate using all years of data:
y=intercept+x1+x2
then use function ME in spdep to find identify Moran eigenvectors to reduce residual SAC using a year specific (index k) spatial weights and year-specific residuals using function ME from spdep package:
EV_k=  ME(residuals_k~1, listw=weights_k), then linearly combine resulting eigenvectors for a given year into a single vector and then concatenate each year's vector such that the final Moran eignevector used in the regression is EV= c(EV_2014,EV_2015,EV_2016)

and add EV as an offset or covariate as in the first equation shown.

This approach seems to work quite well (eliminates residual SAC, doesn't shift regression coefficients substantially, improves model fit), I just don't know if it is statistically sound?

thanks!

        [[alternative HTML version deleted]]

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Re: [DKIM] Random Forest and OOB error [SEC=UNCLASSIFIED]

Mon, 06/04/2018 - 20:24
Hi Waldir,

Please check library(spm). The function RFcv and rgcv  in library(spm) provide you better options to assess the performance of random forest than using OOB error.

Kind regards,
Jin

-----Original Message-----
From: R-sig-Geo [mailto:[hidden email]] On Behalf Of Waldir de Carvalho Junior
Sent: Tuesday, 5 June 2018 3:38 AM
To: [hidden email]
Subject: [DKIM] [R-sig-Geo] Random Forest and OOB error

Hi
how can I get and save the "OOB estimate of  error rate" from the model
randomforest?
I am doing a loop and want to save to each loop the OOB error.
I need to get the value to create a new data.frame with the OOB error from
varios models tests.
Thanks in advance

--
________________________
Waldir de Carvalho Junior

        [[alternative HTML version deleted]]

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Random Forest and OOB error

Mon, 06/04/2018 - 12:38
Hi
how can I get and save the "OOB estimate of  error rate" from the model
randomforest?
I am doing a loop and want to save to each loop the OOB error.
I need to get the value to create a new data.frame with the OOB error from
varios models tests.
Thanks in advance

--
________________________
Waldir de Carvalho Junior

        [[alternative HTML version deleted]]

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regression with Moran eigenvectors for multiple years of data

Mon, 06/04/2018 - 08:12
Hello,

I think this is mostly a statistics question with possibly some R details.
Any feedback is appreciated.

I have several years of spatial biological sampling data in the same region
but the number and locations of sites vary across year.  Very strong
spatial autocorrelation is present in the data.

I want to construct a regression model using Moran' eigenvectors as
explanatory variables to account for SAC. For example,

y_ijk=intercept+x1_ijk+x2_ijk+ EV_k

where x1,x2 are environmental covariates and EV are Moran eigenvectors; i,j
are location and k is year.
Environmental covariate relationships with response variable are assumed
constant across years.

My plan was to first estimate using all years of data:
y=intercept+x1+x2
then use function ME in spdep to find identify Moran eigenvectors to reduce
residual SAC using a year specific (index k) spatial weights and
year-specific residuals using function ME from spdep package:
EV_k=  ME(residuals_k~1, listw=weights_k),
then linearly combine resulting eigenvectors for a given year into a single
vector and then concatenate each year's vector such that the final Moran
eignevector used in the regression is
EV= c(EV_2014,EV_2015,EV_2016)

and add EV as an offset or covariate as in the first equation shown.

This approach seems to work quite well (eliminates residual SAC, doesn't
shift regression coefficients substantially, improves model fit), I just
don't know if it is statistically sound?

thanks!

        [[alternative HTML version deleted]]

_______________________________________________
R-sig-Geo mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/r-sig-geo

Summer School in Geocomputation - Berkeley - USA

Sun, 06/03/2018 - 02:35
Dear colleagues,

the registration is open now for the

*International Summer School:*
*Geocomputation using free and Open Source Software** (20th-24th August
2018) *

organized by Spatial Ecology (www.spatial-ecology.net)
<http://www.spatial-ecology.net/> hosted at the *Berkeley Institute of Data
Science <https://bids.berkeley.edu/>*

A 5 days intense experience opening new horizons on the use of the vast
potentials of *Linux* environment and the command line approach for
*geo-data* massive processing using Bash, AWK, Python, GRASS, QGIS,
GDAL/OGR, R, PKtools. We will guide newbies and experienced GIS users who
have never used a command line terminal to a stage which will allow them to
understand and apply very advanced open source data processing routines.
Our focus is to enhance a self-learning approach. This allows participants
to keep on progressing and improving their skills in a continuously
evolving technological environment.

More information and registration:

www.spatial-ecology.net
www.facebook.com/spatialecology  -> event
<https://www.facebook.com/events/202252593719455/>

twitter: @BigDataEcology

Best regards
Spatial Ecology – Team

--
Giuseppe Amatulli, Ph.D.

Research scientist at
Yale School of Forestry & Environmental Studies
Yale Center for Research Computing
Center for Science and Social Science Information
New Haven, 06511
Teaching: http://spatial-ecology.net
Work:  https://environment.yale.edu/profile/giuseppe-amatulli/

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Re: how to plot different rows of a SpatialPolygonsDataFrame in trellis panels

Fri, 06/01/2018 - 02:29
On Fri, 1 Jun 2018, Edzer Pebesma wrote:

>
>
> On 06/01/2018 05:38 AM, Waichler, Scott R wrote:
>> Kent,
>>
>> Thank you for your response to my problem.  Unfortunately, I can't use
>> sf because it has system dependencies I can't meet.  I am using RHEL 6,
>> and am up-to-date with it for gdal, geos, and proj (versions 1.7.3,
>> 3.3.2, 4.7.0 respectively), but the R package sf requires later
>> versions for all of these.  The vignettes for sf make it sound very
>> useful, but alas it seems to be out of reach for me at present.  I am
>> surprised a package that is being positioned for widespread adoption
>> has such stringent requirements.
>
> According to https://download.osgeo.org/gdal/old_releases/ the gdal
> version you are running is from 2010. You may have followed how gdal has
> improved since 2010, and how it has continuously adapted to the dynamics
> of the geospatial software ecosystem, as well as to the development of
> new geospatial standards. RHEL 6 is EOL in November 2020, so now is the time to move forward. As
Edzer mentions, PROJ, GDAL and GEOS have fixed multiple bugs GDAL has
introduced new drivers over the succession of releases. The GDAL API
changed after 1.11.*, but rgdal does still build with GDAL 1.11.4 and PROJ
4.8.0 (checked recently). From the next (forthcoming) release (1.3.*) of
rgdal, these will be the minimum versions permitted. Even CentOS/RHEL 7
need to install a C++11-capable compiler to build GDAL 2.3.0 - see the
thread at:

https://stat.ethz.ch/pipermail/r-sig-geo/2018-May/026591.html

As Edzer mentions below, users cannot reasonably expect package authors
and maintainers to keep things running in current packages for EOL-near
platforms. If you can provide docker images/containers to emulate near-EOL
platforms (compilers, external dependencies, etc), you can contribute back
to others and protect your workflows by checking systematically that
development versions of sf and rgdal/rgeos can still be installed, pass
R CMD check, and that updates in R packages don't change your results in
other ways than bug-fixes would cause.

We know that institutional users cannot freely upgrade platforms, but RHEL
6 perhaps indicates critical failure to invest by the institution; we know
it happens, but this can't be a priority for package author and maintainer
time.

Roger

>
> I made a deliberate choice to let sf users benefit from these
> improvements by picking gdal 2.0.1 from 2015 as a minimum requirement,
> rather than keep them in the stone ages.
>
> Keeping sf, rgdal and rgeos to work with new releases of gdal, geos and
> proj takes a considerable amount of our time not only for Roger and me,
> but also for the CRAN maintainers. I hope this takes away some of your
> surprise.
>
>>
>> Best,
>> Scott Waichler
>> Pacific Northwest National Laboratory
>> Richland, Washington, USA
>>
>>> -----Original Message-----
>>> From: Kent Johnson [mailto:[hidden email]]
>>> Sent: Thursday, May 24, 2018 6:05 AM
>>> To: [hidden email]; Waichler, Scott R <[hidden email]>
>>> Subject: Re: how to plot different rows of a SpatialPolygonsDataFrame in
>>> trellis panels
>>>
>>> On Thu, May 24, 2018 at 6:00 AM, <[hidden email]> wrote:
>>>
>>> Message: 1
>>> Date: Wed, 23 May 2018 18:39:07 +0000
>>> From: "Waichler, Scott R" <[hidden email]>
>>> To: "[hidden email]" <[hidden email]>
>>> Subject: [R-sig-Geo] how to plot different rows of a
>>>         SpatialPolygonsDataFrame in trellis panels
>>>
>>> Hello,
>>>
>>> I have a SpatialPolygonsDataFrame.  I would like to do a trellis plot on one of
>>> the attributes, so that in the panel for a given attribute value, only those
>>> polygons with that value are plotted.  So, each panel has different polygons
>>> plotted in it.  I can't figure out how to do this.  In the toy example below, I
>>> would like to create a trellis plot with one panel showing the polygons with id
>>> = 1, and another panel showing the polygons with id = 2.
>>>
>>> My goal beyond this toy problem is to do the same thing with stplot, where
>>> panels correspond to times and each time has a different set of polygons
>>> plotted.  Will that be possible?  In all the examples I can find of using stplot
>>> for a space-time grid with the spatial objects being polygons, the polygons
>>> are the same across time.
>>>
>>> # based on example in help("SpatialPolygonsDataFrame-class")
>>> Sr1 = Polygon(cbind(c(2,4,4,1,2),c(2,3,5,4,2)))
>>> Sr2 = Polygon(cbind(c(5,4,2,5),c(2,3,2,2)))
>>> Sr3 = Polygon(cbind(c(4,4,5,10,4),c(5,3,2,5,5)))
>>> Sr4 = Polygon(cbind(c(5,6,6,5,5),c(4,4,3,3,4)), hole = TRUE)
>>> Srs1 = Polygons(list(Sr1), "s1")
>>> Srs2 = Polygons(list(Sr2), "s2")
>>> Srs3 = Polygons(list(Sr3, Sr4), "s3/4")
>>> SpP = SpatialPolygons(list(Srs1,Srs2,Srs3), 1:3)
>>> grd <- GridTopology(c(1,1), c(1,1), c(10,10))
>>> polys <- as(grd, "SpatialPolygons")
>>> centroids <- coordinates(polys)
>>> x <- centroids[,1]
>>> y <- centroids[,2]
>>> z <- 1.4 + 0.1*x + 0.2*y + 0.002*x*x
>>> id = factor(sample(c(1,2), size=length(polys), replace=T))
>>> tmp <- SpatialPolygonsDataFrame(polys,
>>>       data=data.frame(x=x, y=y, z=z, id=id, row.names=row.names(polys)))
>>> plot(tmp)  # plots all the square polygons (n = 10*10)
>>> spplot(tmp)  # plots values of x, y, z, id in separate panels, each with 100
>>> polys
>>> spplot(tmp, zcol=z)  # error message about duplication of factor level
>>> spplot(tmp ~ id, zcol=z, data=tmp)  # won't take formula
>>>
>>> You can do the facetting with ggplot2::geom_sf (in the dev version of
>>> ggplot2) though I don't think it will use different coordinate ranges for
>>> different facets:
>>>
>>> devtools::install_github('tidyverse/ggplot2')
>>> library(sf)
>>> library(ggplot2)
>>> tmp2 = st_as_sf(tmp)
>>>
>>> ggplot(tmp2) + geom_sf(aes(fill=z)) + facet_wrap(~id)
>>>
>>> A couple of suggestions here, using tmap or ggspatial, that look promising:
>>> https://stackoverflow.com/questions/47678480/mapping-different-states-
>>> with-geom-sf-using-facet-wrap-and-scales-free
>>>
>>> Kent Johnson
>>>
>>>
>>> Thank you,
>>> ScottWaichler
>>> Pacific Northwest National Laboratory
>>> scott.waichler _at_ pnnl.gov
>> _______________________________________________
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>>
>
> --
Roger Bivand
Department of Economics, Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; e-mail: [hidden email]
http://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
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Roger Bivand
Department of Economics
Norwegian School of Economics
Helleveien 30
N-5045 Bergen, Norway

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