kernel: gpe kernel class

In goldingn/gpe: Gaussian Process Everything

Description

Generic functions associated with the kernel class.

Usage

is.kernel(x)

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

## S3 method for class 'kernel'
summary(object, ..., digits = max(3, getOption("digits") -
  3))

## S3 method for class 'kernel'
plot(x, which = NULL, range = c(-5, 5), ref = 0, ...)

Arguments

x	a kernel object, or some other object to be tested
object	a kernel object
digits	the number of digits to display for the kernel parameters
which	a string giving the column name for which to plot the covariance structure. If NULL a plot will be produced for each caolumn on which the kernel acts
range	the range of distances between points over which to plot covariances
ref	the reference value against which to compare other points of a given distance
...	additional arguments for compatibility with generic functions

Details

is.kernel returns a logical indicating whether the object is a gpe kernel. print returns a very simple summary of the kernel structure. summary returns a more detailed summary of the kernel structure, including the values of the kernel parameters. plot plots the covariance structure of the kernel (how covariance) between two points depends on the distance between them.

Examples

 
# construct a kernel with one feature
k1 <- rbf('temperature')
 

# is it a kernel? 
is.kernel(k1)
 
 
# print the kernel's basic structure
print(k1)
 
# this is also the default action for displaying the object:
k1
  
 
# a more detailed summary of the kernel's structure
summary(k1)
 
 
# plot the covariance structure of the GP
plot(k1)

goldingn/gpe documentation built on May 17, 2019, 7:41 a.m.