View source: R/kmMonotonic1D.R
kmMonotonic1D | R Documentation |
kmMonotonic1D(design, response, basis.size = dim(design)[1] + 2 + 10,
covtype = "matern5_2", basis.type = "C1", coef.cov = 0.5 * (max(design)
- min(design)), coef.var = var(response), 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) |
basis.type |
an optimal character string specifying the regularization of the basis functions to be used (which implies the class of the simulation paths) |
coef.cov |
a value corresponding to the length theta hyper-parameters of covariance function |
coef.var |
a value specifying the variance parameter |
nugget |
an optimal value used as nugget effect to solve the numerical inverse matrix problem |
kmMonotonic1D(design=c(0.1, 0.5, 0.9), response=c(1, 5, 9))
kmMonotonic1D(design=c(0.1, 0.5, 0.9), response=c(1, 5, 9), basis.type="C0")
kmMonotonic1D(design=sort(runif(5)), response=cumsum(runif(5)), nugget=1e-4, covtype="gauss")
f <- function(x){
log(20*x+1)
}
design <- c(0, 0.1, 0.2, 0.3, 0.4, 0.9, 1)
response <- f(design)
meany <- mean(response)
f <- function(x){
log(20*x+1)-meany
}
design <- c(0, 0.1, 0.2, 0.3, 0.4, 0.9, 1)
response <- f(design)
model = kmMonotonic1D(design, response, coef.var=335^2, coef.cov=4.7,basis.size=50)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.