Variance applied to simulation responses


  • Alias: None

  • Arguments: REALLIST

  • Default: no variance


The variance that is applied to simulations run by Dakota, i.e. using the analysis_drivers command. The user may supply a single variance or a vector of variances of length equal to the number of responses. In both cases, the values provided are treated as scalar variance types. If a single variance is provided, it is applied to all responses produced by the simulation code. If a vector is provided, each variance is applied to the corresponding response output produced by the simulation code.

It is important to note that the the variance defined by this keyword differs from that defined using experiment_variance_type. These two commands apply to user-provided calibration data, specified, for example, by calibration_data or calibration_data_file. However, simulation_variance applies to those responses produced by simulation code that is run by Dakota, as described above.

Usage Tips

Currently, this keyword is only in use as part of the algorithm implemented by experimental_design. In this algorithm, two models (usually, one high-fidelity and one low-fidelity) are provided to Dakota, each with their own responses section of the input script, and each of which is allowed its own simulation_variance. The variance specified in the responses block belonging to the high-fidelity model is applied to any <i> new </i> high-fidelity data that is produced by Dakota running the high-fidelity model. In the experimental_design algorithm, low-fidelity model responses are used during the calibration of the model parameters, the calculation of the mutual information, and the calculation of any posterior statistics after the algorithm is complete. The simulation_variance is applied to the low-fidelity model responses that are used in the calculation of the mutual information. See the User’s and Theory Manuals for more information.


The example below shows two responses blocks, one for the low-fidelity model and one for the high-fidelity model. Both contain simulation_variance commands that will apply to the low- and high-fidelity model responses, respectively.

  id_responses = 'low-fidelity'
 calibration_terms = 1
 simulation_variance = 0.5

  id_responses = 'high-fidelity'
  calibration_terms = 1
 calibration_data_file = 'dakota_bayes_expdesign.dat'
   num_config_variables = 1
   num_experiments = 1
   experiment_variance_type = 'none'
 simulation_variance = 1.2