title: multivariate Mann-Whitney U test
body: <p>Good day. I am search for some help/suggestions with a data set I have, for which I want to run a Mann-Whitney U test. A dummy set of the data.frame looks like this:</p>
  
  <pre><code> Plant R1 R2 R3 R4 R5
       a  1  2  3  4  5
       a  6  7  8  9 10
       a 11 12 13 14 15
       b 16 17 18 19 20
       b 21 22 23 24 25
       b 26 27 28 29 30
       b 31 32 33 34 35
       c 36 37 38 39 40
       c 41 42 43 44 45
       c 46 47 48 49 50
       d 51 52 53 54 55
       d 56 57 58 59 60
  </code></pre>
  
  <p>I have 26 different plants and  I would like to test the hypothesis that between all pairs of plant species (a,b,c...etc) there is no significant difference between the median reflectance of each individual waveband (r1,r2,r3...r400.There are 400 waveband columns). The hypothesis is to be tested 325 times for all possible combination of 26 plant species. The null hypothesis should be tested at significance level of ά = 0.00015 (to correct for the Bonferroni effect, 0.05/325). </p>
  
  <p>I am aware of the <code>wilcox.test</code> command to perform a pairwise comparison. I tried searching the Cran repository and found <code>npmc</code> package, but it is no longer maintained.  </p>
  
  <p>I would like the result to look like this:</p>
  
  <pre><code>Comparison   R1   R2   R3   R4   R5
      ab      p-value
      ac
      ad
  </code></pre>
  
  <p>But I have no idea where to begin. Can anyone offer any suggestions please. Thanks in advance.</p>
  
  <p>Kurt</p>