title: Principal Components Analysis - how to get the contribution (%) of each parameter to a Prin.Comp.?
body: <p>I want to know to what degree a measurement/parameter contributes to one of the calculated principal components.</p>
  
  <p>A real-world description:</p>
  
  <ol>
  <li>i've got five climatic parameters to the geographic distribution of a species</li>
  <li>i performed a PCA with these five parameters</li>
  <li>the plot of the PC1 vs. PC2 shows an interesting pattern</li>
  </ol>
  
  <p>Question: How do I get the percentage of contribution (of each parameter) to each PC?</p>
  
  <p>What I expect: PC1 is composed to 30% of parameter1, to 50% of parameter2, to 20% of parameter3, 0% of parameter4 and 0% of parameter5. PC2 is composed...</p>
  
  <p>An example with 5 dummy-parameters:</p>
  
  <pre><code>a &lt;- rnorm(10, 50, 20)
  b &lt;- seq(10, 100, 10)
  c &lt;- seq(88, 10, -8)
  d &lt;- rep(seq(3, 16, 3), 2)
  e &lt;- rnorm(10, 61, 27)
  
  my_table &lt;- data.frame(a, b, c, d, e)
  
  pca &lt;- princomp(my_table, cor=T)
  
  biplot(pca) # same: plot(pca$scores[,1], pca$scores[,2])
  
  pca
  summary(pca)
  </code></pre>
  
  <p>Where is my information hidden?</p>