Dakota Reference Manual
Version 6.4
LargeScale Engineering Optimization and Uncertainty Analysis

Discrete, epistemic uncertain variable  real numbers within a set
This keyword is related to the topics:
Alias: none
Argument(s): INTEGER
Default: no discrete uncertain set real variables
Required/Optional  Description of Group  Dakota Keyword  Dakota Keyword Description  

Optional  elements_per_variable  Number of admissible elements for each set variable  
Required  elements  The permissible values for each discrete variable  
Optional  set_probabilities  This keyword defines the probabilities for the various elements of discrete sets.  
Optional  categorical  Whether the setvalued variables are categorical or relaxable  
Optional  initial_point  Initial values  
Optional  descriptors  Labels for the variables 
Discrete set variables may be used to specify categorical choices which are epistemic. For example, if we have three possible forms for a physics model (model 1, 2, or 3) and there is epistemic uncertainty about which one is correct, a discrete uncertain set may be used to represent this type of uncertainty.
This variable is defined by a set of reals, in which the discrete variable may take any value defined within the real set (for example, a parameter may have two allowable real values, 3.285 or 4.79).
Other epistemic types include:
Let d1 be 2.1 or 1.3 and d2 be 0.4, 5 or 2.6. The following specification is for an interval analysis:
discrete_uncertain_set integer num_set_values 2 3 set_values 2.1 1.3 0.4 5 2.6 descriptors 'dr1' 'dr2'
The discrete_uncertain_setinteger
variable is NOT a discrete random variable. It can be contrasted to a the histogramdefined random variables: histogram_bin_uncertain and histogram_point_uncertain. It is used in epistemic uncertainty analysis, where one is trying to model uncertainty due to lack of knowledge.
The discrete uncertain set integer variable is used in both interval analysis and in DempsterShafer theory of evidence.