text: Title: question: how do I select the optimum number of resamples value to use?
  Body: Hi,
  
  It may be possible that the results of Sobol, Morris, Delta-Moment, and Derivative-based Global Sensitivity Measure depend on the used number of resamples value. If this is the case, is there a way to estimate the optimum value?
  
  For example, I have this problem definition:
  problem= {
          'num_vars': 6,
          'names': ['Amplitude', 'Bandwidth', 'Envelope', 'Instantaneous Frequency', 'Sweetness', 'Thin Bed'],
          'bounds': [[min_amplitude, max_amplitude],
                     [min_bandwidth, max_bandwidth],
                     [min_envelope, max_envelope],
                     [min_instantaneous_frequency, max_instantaneous_frequency],
                     [min_sweetness, max_sweetness],
                     [min_thin_bed, max_thin_bed]],
          'distributions': ['norm', 'norm', 'norm', 'norm', 'norm', 'norm']
          }
  
  The input and model data is in a 2D array of size 7344 x 7. The last column contains the model output.
  
  What would be the optimum value for the number of resamples? is there a formula that I can use?
  
  Many thanks,
  Ivan
  