Method

Equation Available

Highly Nonlinear

Noisy Output Responses

Accuracy

Efficiency

Basic Parameters

Comments

Least Square Regression

Order should be adjusted and regression terms may be picked.

Noises can be screened out with this method.

Moving Least Squares Method

Order should be adjusted.

The time to build the fit and use the fit (Evaluate From) increases with both the number of runs and the number of input variables in the input matrix. The number of input variables has more influence than the number of runs if order is larger than 1.

HyperKriging

The time to build the fit and use the fit (Evaluate From) increases with both the number of runs and the number of input variables in the input matrix. The number of input variables has more influence than the number of runs if order is larger than 1.

Radial Basis Function

The time to build the fit increases with both the number of runs and the number of input variables in the input matrix. The number of runs has more influence than the number of input variables. The run time for using the fit in another approach (Evaluate From) is very small regardless of the size of the input matrix.