summary.gp: Gaussian Process Summary Information

In mlegp: Maximum Likelihood Estimates of Gaussian Processes

Gaussian Process Summary Information

Description

prints a summary of a Gaussian process object

Usage

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

Arguments

object	an object of class gp
...	for compatibility with generic method summary

Details

prints a summary of the Gaussian process object object. Output should be self explanatory, except for possibly CV RMSE, the cross-validated root mean squared error (the average squared difference between the observations and cross-validated predictions); and CV RMaxSE, the maximum cross-validated root squared error. If the design in the Gaussian process object contains any replicates, the root mean pure error (RMPE), which is the square root of the average within replicate variance and the root max pure error (RMaxPE) are also reported.

Author(s)

Garrett M. Dancik [e-mail]

References

https://github.com/gdancik/mlegp/

See Also

createGP for details of the Gaussian process object

Examples

## no replicates in the design matrix ##
x1 = -5:5; y1 = sin(x1) + rnorm(length(x1),sd=.1)
fit1 = mlegp(x1, y1)
summary(fit1)

## with replicates in the design matrix ##
x2 = kronecker(x1, rep(1,3)) 
y2 = sin(x2) + rnorm(length(x2), sd = .1)
fit2 = mlegp(x2,y2)
summary(fit2)

mlegp documentation built on March 18, 2022, 5:29 p.m.