title: R: adjusting a given time-series but keeping summary statistics equal
body: <p>Let's say I have a time-series like this</p>
  
  <pre><code>t       x
  1       100
  2       50
  3       200
  4       210
  5       90
  6       80
  7       300
  </code></pre>
  
  <p>Is it possible in R to generate a new dataset <code>x1</code> which has the exact same summary statistics, e.g. mean, variance, kurtosis, skew as <code>x</code>? </p>
  
  <p>The reason for my asking is that I would like to do an experiment where I want to test how subjects react to different graphs of data that contain the same information.</p>
  
  <p>I recently read:</p>
  
  <ul>
  <li><p>Matejka, Justin, and George Fitzmaurice. "Same stats, different graphs: Generating datasets with varied appearance and identical statistics through simulated annealing." Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 2017.</p></li>
  <li><p>Generating Data with Identical Statistics but Dissimilar Graphics: A Follow up to the Anscombe Dataset, The American Statistician, 2007,</p></li>
  </ul>
  
  <p>However, Matejka uses code in Python that is quite scientific and their data is more complex than time-series data, so I was wondering if there was a way to do this more efficiently for a simpler data set?</p>
  
  <p>Best regards</p>