Download User guide for Modularized Surrogate Model Toolbox

Output:
Variable
Description
lambda, gamma
dmodel
mmodel
beta
wm
vectors, parameters of RBF model; lambda=gamma=[] if RBF model not used
structure, parameters for kriging model; dmodel=[] if kriging model not used
structure, parameters for MARS model; mmodel=[] if MARS model not used
vector, parameters of polynomial regression model; beta=[] if polynomial model not used
vector, contains the weights for the models in mixtures; w m=[] if no mixture model used
RBF.m and RBF eval.m
The parameters of the radial basis function (RBF) interpolant are computed by the function RBF.m,
and RBF eval.m predicts the objective function values using the RBF surrogate model.
Input RBF.m:
Variable
Description
S
Y
flag
matrix, contains the sample points
column vector, contains function values corresponding to points in S
string, determines what type of RBF interpolant is used (see Table 3)
Output RBF.m:
Variable
Description
lambda
gamma
column vector, contains multipliers of radial basis functions
column vector, contains parameters for polynomial tail
11