Number of bins used to compute the variance-based decomposition


  • Alias: None

  • Arguments: INTEGER

  • Default: -1


Allows the user to specify the number of bins to be used in the variance-based decomposition.

Default Behavior Default number of bins is the square root of the number of samples rounded down to the nearest integer.


    sample_type lhs
    samples = 100
      vbd_method binned
        num_bins = 10


The binned approach to computing Sobol’ main effect indices is introduced in [LM16]. As opposed to pick-and-freeze approaches like [STCR04], it does not require a specific sampling structure. Given a set of randomly-generated input-output samples, it computes the main effect index by binning samples, computing a sample statistic for each bin, then computing another sample statistic over the bins.

The number of bins recommended in [LM16] is the square root of the number of input-output samples. This is the default number of bins used for the method in Dakota. However, if the user wishes to specify a different number of bins, they can do so using num_bins.