Release v0.8.1 on CRAN

In this release,

• convexjlr supports Julia v0.7 and v1.0 as well as Julia v0.6.
• Drop XRJulia support, as it does not work with Julia v0.7 and v1.0.
• Users can choose ECOS as the solver for convex problems.
• Users can set a bunch of options for both SCS and ECOS solvers.
• Various bug fixes.

v0.7.0 release on CRAN

In this release,

• Remove deprecated setup function.
• Use JuliaCall as the default backend.
• Fix deprecation warnings from JuliaCall backend.
• Fix some little bugs.
• Add the option in convex_setup to set the path to julia binary.

v0.6.1 Supports Multiple Backends

The main difference in this release compared to the last one

• Deprecate setup, should use convex_setup.

• Supports multiple ways to connect to 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.

First CRAN version

This is my first submission to CRAN!