summary.GP: Summary of GP model fit

In GPfit: Gaussian Processes Modeling

Description

Prints the summary of a class GP object estimated by GP_fit

Usage

## S3 method for class 'GP'
summary(object, ...)

Arguments

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

Details

prints the summary of the GP object (object), by calling print.GP

Author(s)

Blake MacDonald, Hugh Chipman, Pritam Ranjan

See Also

print.GP for more description of the output;
GP_fit for more information on estimating the model;
summary for more description on the summary 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)
summary(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 <- 10
d <- 2
set.seed(1)
x <- lhs::maximinLHS(n, d) 
y <- computer_simulator(x)
GPmodel <- GP_fit(x, y)
summary(GPmodel)

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