print.GP: GP model fit Summary

In GPfit: Gaussian Processes Modeling

Description

Prints the summary of a class GP object estimated by GP_fit

Usage

## S3 method for class 'GP'
print(x, ...)

Arguments

x	a class GP object estimated by GP_fit
...	for compatibility with generic method print

Details

Prints the summary of the class GP object. It returns the number of observations, input dimension, parameter estimates of the GP model, lower bound on the nugget, and the nugget threshold parameter (described in GP_fit).

Author(s)

Blake MacDonald, Hugh Chipman, Pritam Ranjan

See Also

GP_fit for more information on estimating the model;
print for more description on the print function.

Examples

## 1D example
n <- 5
d <- 1 
computer_simulator <- function(x){
    x <- 2 * x + 0.5
    y <- sin(10 * pi * x) / (2 * x) + (x - 1)^4
    return(y)
}
set.seed(3)
x <- lhs::maximinLHS(n, d)
y <- computer_simulator(x)
GPmodel <- GP_fit(x, y)
print(GPmodel)


## 2D Example: GoldPrice Function
computer_simulator <- function(x) {
    x1 <- 4*x[,1] - 2
    x2 <- 4*x[,2] - 2
    t1 <- 1 + (x1 + x2 + 1)^2*(19 - 14*x1 + 3*x1^2 - 14*x2 + 
        6*x1*x2 + 3*x2^2)
    t2 <- 30 + (2*x1 -3*x2)^2*(18 - 32*x1 + 12*x1^2 + 48*x2 - 
        36*x1*x2 + 27*x2^2)
    y <- t1*t2
    return(y)
}
n <- 30 
d <- 2
set.seed(1)
x <- lhs::maximinLHS(n, d) 
y <- computer_simulator(x)
GPmodel <- GP_fit(x,y)
print(GPmodel, digits = 3)

GPfit documentation built on May 2, 2019, 5:31 a.m.