r - How to test all sample combinations for significant differences? -


i'm analyzing dataset of 9 plots in r , want compare them each other. responding variables not distributed.

now question:

there 9+8+7+...+2+1=45 pair-combinations tested. can r automatically? if yes, how? wish-output box-whisker plot 9 plots on x-axis, responding variable on y-axis , lowercase letters above plots indicate significant differences.

thanks in advance!

this should started:

#some data x <- rlnorm(100, mean=1:4) df <- data.frame(x=x, g=c("a", "b", "c", "d"), stringsasfactors=false)  #pairwise mann-whitney-u-test pairwise.wilcox.test(df$x, df$g, p.adjust.method = "bonferroni")  #   pairwise comparisons using wilcoxon rank sum test  # #data:  df$x , df$g  # #        b       c      #b 0.0016  -       -      #c 6.3e-09 0.0020  -      #d 1.9e-13 2.0e-08 0.1823 # #p value adjustment method: bonferroni

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