RinRuby is a bridge bewteen Ruby and R, and this is the forked version.
Clone or download
Pull request Compare This branch is 18 commits ahead of clbustos:master.
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
lib
spec
.appveyor.yml
.gitignore
.travis.yml
Gemfile
History.txt
LICENSE.txt
Manifest.txt
README.md
Rakefile
rinruby.gemspec

README.md

rinruby

Build Status

Build status

This is a forked version of RinRuby. The advantage of this forked version is mainly addition of functionality.

Specific information of this version

INSTALL

LICENSE (same as the original version)

GPL-3. See LICENSE.txt for more information.

Original information (copied)

DESCRIPTION

RinRuby is a Ruby library that integrates the R interpreter in Ruby, making R's statistical routines and graphics available within Ruby. The library consists of a single Ruby script that is simple to install and does not require any special compilation or installation of R. Since the library is 100% pure Ruby, it works on a variety of operating systems, Ruby implementations, and versions of R. RinRuby's methods are simple, making for readable code. The website rinruby.ddahl.org describes RinRuby usage, provides comprehensive documentation, gives several examples, and discusses RinRuby's implementation.

Copyright 2005-2008 David B. Dahl

Developed by David B. Dahl. Documented by David B. Dahl and Scott Crawford

Homepage: http://rinruby.ddahl.org

Maintainer: Claudio Bustos

Contributors:

FEATURES/PROBLEMS

  • Pure Ruby. Works on Ruby 2.1, 2.2, 2.4 and JRuby-head (2018/03/29). There isn't any specific code that impides to use Ruby < 2.0, but is deprecated.
  • Slower than RSRuby, but more robust

SYNOPSIS

Below is a simple example of RinRuby usage for simple linear regression. The simulation parameters are defined in Ruby, computations are performed in R, and Ruby reports the results. In a more elaborate application, the simulation parameter might come from input from a graphical user interface, the statistical analysis might be more involved, and the results might be an HTML page or PDF report.

Code

  require "rinruby"
  n = 10
  beta_0 = 1
  beta_1 = 0.25
  alpha = 0.05
  seed = 23423
  R.x = (1..n).entries
  R.eval <<EOF
      set.seed(#{seed})
      y <- #{beta_0} + #{beta_1}*x + rnorm(#{n})
      fit <- lm( y ~ x )
      est <- round(coef(fit),3)
      pvalue <- summary(fit)$coefficients[2,4]
  EOF
  puts "E(y|x) ~= #{R.est[0]} + #{R.est[1]} * x"
  if R.pvalue < alpha
    puts "Reject the null hypothesis and conclude that x and y are related."
  else
    puts "There is insufficient evidence to conclude that x and y are related."
  end

Output

  E(y|x) ~= 1.264 + 0.273 * x
  Reject the null hypothesis and conclude that x and y are related.

REQUIREMENTS

  • R