Nothing
Julia
v0.7 and v1.0.XRJulia
support, as it does not work with Julia
v0.7 and v1.0.SCS
solver doesn't have verbose = FALSE
default option any more.ECOS
as the solver for convex problems.SCS
and ECOS
solvers.cvx_optim
.diag
.setup
function.JuliaCall
as the default backend.JuliaCall
backend.convex_setup
to set the path to julia
binary.julia
, one way is through package XRJulia
,
and the other way is to use package JuliaCall
. The difference is as follows:XRJulia
connects to julia
, which is the default for convexjlr
,
the advantage is the simplicity of the installation process, once you have a working
R and working julia, it should be okay to use convexjlr
in this way. Note that
if you have the latest Julia version (v0.6.0) installed, then you have to use the
latest version of XRJulia
.JuliaCall
embeds julia
in R,
the advantage is the performance, for example,
if your convex problem involves large matrice or long vectors,
you may wish to use JuliaCall
backend for convexjlr
;
the disadvantage is the installation process, since embedding julia
needs
compilations.NEWS.md
file to track changes to the package.setup
, should use convex_setup
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