title: How to calculate the quality of clustering by dtw?
body: <p>my aim is to cluster 126 time-series concerning 26 weeks (so each time-series has 26 observation). I used <code>pam{cluster}</code> = partitioning around medoids to cluster these time-series. </p>
  
  <p>Before clustering I wanted to compare which distance measure is the most appropriate: euclidean, manhattan or dynamic time warping. I used each distance to cluster and compare by silhouette plot. Is there any way I can compare different distance measure? </p>
  
  <p>For example I know that procedure <code>clValid {clValid}</code> to validate cluster results, however I cannot implement dtw to calculate indexes.</p>
  
  <p>So how can I compare different distance metrics (not only by silhouette)?</p>
  
  <p>Additional question: is GAP statistic enough to decide how many clusters choose? Or should I evaluate number of clusters with different methods or compare two or three ways how to do it?</p>
  
  <p>I would be grateful for any suggestions.</p>