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# As another example of Ruby Rserve client, extracted from RinRuby documentation, consider the usage of Ruby Rserve client for simple linear regression below. The simulation parameters are deļ¬ned in Ruby, computations are performed in R, and Ruby reports the results. In a more eloborate 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.
require 'rserve'
r=Rserve::Connection.new
n = 10
beta_0 = 1
beta_1 = 0.25
alpha = 0.05
seed = 23423
# You could assign a ruby object to a R variable automaticly. You could see
# the rules of translation on Rserve::REXP::Wrapper module
r.assign "x", (1..n).entries
# Rserve::Connection.void_eval allows you to send complex R commands
# without wasting time retrieving the final result
r.void_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)$coefficients[2,4]
EOF
# Rserve::Connecttion.eval retrieve a Rserve::REXP object, which could
# be translated to an appropiate Ruby object using Rserve::REXP.to_ruby method
#
est=r.eval("est").to_ruby
# fit$coef is a named doubles vector, so the respective Ruby object is an
# array of rational extended with module WithNames. That allows us
# to retrieve every element of the vector by its name
puts "E(y|x) ~= #{est['(Intercept)'].to_f} + #{est['x'].to_f} * x"
# fit$pvalue is a vector of size 1. So, the method #to_ruby
# retrieves a rational or a Fixnum, according to original representation
if r.eval("pvalue").to_ruby < 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
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12 entries across 12 versions & 1 rubygems