1 2 3 4 5 | kmBounded1D(design, response, basis.size = dim(design)[1] + 2 + 10,
covtype = "matern5_2", coef.cov = 0.5 * (max(design) - min(design)),
coef.var = var(response), lower = min(response) - (max(response) -
min(response)) * 0.1, upper = max(response) + (max(response) -
min(response)) * 0.1, nugget = 1e-07 * sd(response))
|
design |
1-column matrix of the design of experiments |
response |
a vector containing the output values given by the real function at the design points |
basis.size |
a value represents the number of the basis functions (descritization of 1D input set) |
covtype |
an optimal character string specifying the covariance function to be used ("gauss" and "matern3_2" choice) |
coef.cov |
a value corresponding to the length theta hyper-parameters of covariance function |
coef.var |
a value specifying the variance parameter |
lower |
lower bound constraint |
upper |
upper bound constraint |
nugget |
an optimal value used as nugget effect to solve the numerical inverse matrix problem |
1 | model = kmBounded1D(design=c(0.1, 0.3, 0.5, 0.9), response=c(7, -8, 9, 15), lower=-10, upper = 18, coef.cov=1)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.