This is an R package that provides a single interface for many different Gaussian process modeling software options.
This package was formerly called UGP, for Universal Gaussian processes, but universal has a different meaning in kriging so the name was changed for clarity.
You can install IGP from GitHub with:
# install.packages("devtools")
devtools::install_github("CollinErickson/IGP")
The following shows a simple example using the R package laGP as the
GP code.
set.seed(0)
library(IGP)
package = "laGP"
n <- 20
d <- 1
f1 <- function(x) {abs(sin(2*pi*x[1]))}
X1 <- matrix(runif(n*d),n,d)
Z1 <- apply(X1,1,f1) + rnorm(n, 0, 1e-3)
gp <- IGP(package=package,X=X1,Z=Z1)
curve(sapply(x, f1), ylab='y')
curve(gp$predict(matrix(x, ncol=1)) - 2 * gp$predict.se(matrix(x, ncol=1)), col=3, add=T)
curve(gp$predict(matrix(x, ncol=1)) + 2 * gp$predict.se(matrix(x, ncol=1)), col=3, add=T)
curve(gp$predict(matrix(x, ncol=1)), col=2, add=T)
points(X1, Z1, pch=19)
Below is the exact same thing except using the R package GauPro. The
predictions made are indistinguishable, meaning that they have fit
approximately the same parameter values.
set.seed(0)
package = "GauPro"
gp <- IGP(package=package,X=X1,Z=Z1)
curve(sapply(x, f1), ylab='y')
curve(gp$predict(matrix(x, ncol=1)) - 2 * gp$predict.se(matrix(x, ncol=1)), col=3, add=T)
curve(gp$predict(matrix(x, ncol=1)) + 2 * gp$predict.se(matrix(x, ncol=1)), col=3, add=T)
curve(gp$predict(matrix(x, ncol=1)), col=2, add=T)
points(X1, Z1, pch=19)
The available packages and the platform they run on are shown below. The
R packages should run easily. The MATLAB packages are called using the
R.matlab R package and have to open a connection to MATLAB. Thus you
need to have MATLAB on your computer, it will be slow, and is likely to
have problems. Currently the MATLAB packages are not included in the
CRAN version of the package, but they can be found on the GitHub
repository. The Python packages are called using the R package
Python.In.R. It will open a connection to Python and probably will be
slow. In addition to requiring that you already have the package (GPy or
sklearn) installed, and must be accessible through your default Python
path.
| Package | Platform |
|---|---|
| DiceKriging | R |
| GauPro | R |
| GPfit | R |
| laGP | R |
| mlegp | R |
| tgp | R |
| DACE (GitHub only) | MATLAB |
| GPML (GitHub only) | MATLAB |
| GPy | Python |
| sklearn | Python |