Comments (7)
Hi and thanks for reporting the issue!
I am also on OSX and I have no problem to install with gcc. However, I just tried clang and can't install either, so the issue is definitely with the compiler. I also just noticed that the same thing is happening in the CRAN build, so you're not alone ;)
I am trying to understand what happened in the new version of vinecopulib, but in the meantime, you can do for instance brew install gcc
and then add
CC=/usr/local/bin/gcc-7
CXX=/usr/local/bin/g++-7
or something similar in .R/Makevars
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Thomas, it appears that the problem comes from those lines
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Also, since most macOS users won't be able to install as long as this is not resolved, it's a bit urgent. I should really test the package using clang or we should set-up travis for OSX, because this is really bad.
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I guess this is a good opportunity to test #69. Bo, could you try installing with
devtools::install_github("vinecopulib/rvinecopulib", ref = "cout-init")
?
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It worked on my computer.
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Thanks @tnagler and @tvatter for your quick response! I can successfully install the dev branch now.
I got the following warning at the end of installation, not sure if it's critical.
Warning in FUN(X[[i]], ...) : internal error -3 in R_decompress1
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Hm, I've never seen this message before and google doesn't seam to help either (found something like this). As long everything else works, I will assume it's not critical and close this issue ;)
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Related Issues (20)
- Links to vinecop-methods in vinecop docs HOT 1
- Support for fitting parametric margins HOT 2
- Code coverage
- Cannot install version 0.5.2.1.0 on Linux Iridis 5 HOT 5
- Unexpected behaviour of vinecop() HOT 2
- Automatic Threshold selection without automatic truncation causes error HOT 2
- Evaluating copula density --> NaN and inaccuracies HOT 3
- plot font size selection HOT 1
- Documentation wrong for bicop_dist Student t Distribution
- no function to create random generator like Mvdc in Copula HOT 2
- kernel copula HOT 2
- Is there possibility to implement kernel copula with dimensions >2? HOT 1
- Bug in compute_pseudo_obs for discrete variables HOT 2
- bicop and BiCopSelect return different models HOT 1
- difference between vine and vinecop HOT 2
- Restriction of rotations in automatic fitting
- Sampling HOT 8
- the selection of best-fit model HOT 2
- Typo in the documentation of `emp_cdf`
- Distribution logis not handled HOT 1
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