title: How do I assign weights using Kernel function based on a vector of pairwise Euclidean distance?
body: <p>I want to quantify the dissimilarity between two group. Each group has 5 observations, so there are 25 combinations.</p>
  
  <p>For each combination, I have calculated their pairwise Euclidean distance (based on feature space). So I have had a vector of pairwise Euclidean distances as follows:</p>
  
  <pre><code>set.seed(1)
  runif(n=25, min=50, max=90)
   [1] 60.62035 64.88496 72.91413 86.32831 58.06728 85.93559 87.78701 76.43191 75.16456 52.47145 58.23898 57.06227 77.48091
  [14] 65.36415 80.79366 69.90797 78.70474 89.67624 65.20141 81.09781 87.38821 58.48570 76.06695 55.02220 60.68883
  </code></pre>
  
  <p>I want to use Kernel function to assign weights to the 25 combinations based on the vector of pairwise Euclidean distances. Shorter distance, larger weight.</p>
  
  <p>How can I do it in R? </p>
  
  <p>I have limited knowledge about kernel. Thank you in advance for any suggestions! </p>
  
  <p>I would really appreciated it even if you can give me some hints about the mathematical formula without any programming.</p>