title: Randomization test for size of 'holes' in spatial survivorship data
body: <p>I have survivorship data (binomial) for individuals across a morphological space (fish skull shapes). I'd like to design a test to see if local areas of death in this space are larger than expected by chance. The probability of a single group of observed deaths could be simply computed from the binomial distribution (one-tailed). However, I am interesting in comparing against holes of similar magnitude anywhere within the space, not just in the observed position (many-tailed test). What is the best way to code this in R?</p>
  
  <p>So, for example: given 100 survivors out of 1000 individuals, each with a unique position in a two-dimensional space, I can draw 1000 random samples and randomize which individuals survive in each, holding constant the total number of survivors and their position in two-dimensional space in each sample. </p>
  
  <p>In each of these samples (100 random survivors within a fixed space of 1000 individuals), I would then like to find the largest spatial region which contains no survivors. In the simplest case, this region could be constrained to be an ellipse. At this point, I'm not sure how to best code this test statistic? </p>
  
  <p>The significance of the size of observed holes could then be compared to the number of random samples containing holes of equal or larger size.</p>
  
  <p>Thanks for your help!</p>