IgnoreIndsKernel: Kernel R6 class

IgnoreIndsKernelR Documentation

Kernel R6 class

Description

Kernel R6 class

Kernel R6 class

Usage

k_IgnoreIndsKernel(k, ignoreinds, useC = TRUE)

Arguments

k

Kernel to use on the non-ignored indices

ignoreinds

Indices of columns of X to ignore.

useC

Should C code used? Not implemented for IgnoreInds.

Format

R6Class object.

Value

Object of R6Class with methods for fitting GP model.

Super class

GauPro::GauPro_kernel -> GauPro_kernel_IgnoreInds

Public fields

D

Number of input dimensions of data

kernel

Kernel to use on indices that aren't ignored

ignoreinds

Indices to ignore. For a matrix X, these are the columns to ignore. For example, when those dimensions will be given a different kernel, such as for factors.

Active bindings

s2_est

Is s2 being estimated?

s2

Value of s2 (variance)

Methods

Public methods

Inherited methods

Method new()

Initialize kernel object

Usage
IgnoreIndsKernel$new(k, ignoreinds, useC = TRUE)
Arguments
k

Kernel to use on the non-ignored indices

ignoreinds

Indices of columns of X to ignore.

useC

Should C code used? Not implemented for IgnoreInds.


Method k()

Calculate covariance between two points

Usage
IgnoreIndsKernel$k(x, y = NULL, ...)
Arguments
x

vector.

y

vector, optional. If excluded, find correlation of x with itself.

...

Passed to kernel


Method kone()

Find covariance of two points

Usage
IgnoreIndsKernel$kone(x, y, ...)
Arguments
x

vector

y

vector

...

Passed to kernel


Method dC_dparams()

Derivative of covariance with respect to parameters

Usage
IgnoreIndsKernel$dC_dparams(params = NULL, X, ...)
Arguments
params

Kernel parameters

X

matrix of points in rows

...

Passed to kernel


Method C_dC_dparams()

Calculate covariance matrix and its derivative with respect to parameters

Usage
IgnoreIndsKernel$C_dC_dparams(params = NULL, X, nug)
Arguments
params

Kernel parameters

X

matrix of points in rows

nug

Value of nugget


Method dC_dx()

Derivative of covariance with respect to X

Usage
IgnoreIndsKernel$dC_dx(XX, X, ...)
Arguments
XX

matrix of points

X

matrix of points to take derivative with respect to

...

Additional arguments passed on to the kernel


Method param_optim_start()

Starting point for parameters for optimization

Usage
IgnoreIndsKernel$param_optim_start(...)
Arguments
...

Passed to kernel


Method param_optim_start0()

Starting point for parameters for optimization

Usage
IgnoreIndsKernel$param_optim_start0(...)
Arguments
...

Passed to kernel


Method param_optim_lower()

Lower bounds of parameters for optimization

Usage
IgnoreIndsKernel$param_optim_lower(...)
Arguments
...

Passed to kernel


Method param_optim_upper()

Upper bounds of parameters for optimization

Usage
IgnoreIndsKernel$param_optim_upper(...)
Arguments
...

Passed to kernel


Method set_params_from_optim()

Set parameters from optimization output

Usage
IgnoreIndsKernel$set_params_from_optim(...)
Arguments
...

Passed to kernel


Method s2_from_params()

Get s2 from params vector

Usage
IgnoreIndsKernel$s2_from_params(...)
Arguments
...

Passed to kernel


Method print()

Print this object

Usage
IgnoreIndsKernel$print()

Method clone()

The objects of this class are cloneable with this method.

Usage
IgnoreIndsKernel$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

kg <- Gaussian$new(D=3)
kig <- GauPro::IgnoreIndsKernel$new(k = Gaussian$new(D=3), ignoreinds = 2)
Xtmp <- as.matrix(expand.grid(1:2, 1:2, 1:2))
cbind(Xtmp, kig$k(Xtmp))
cbind(Xtmp, kg$k(Xtmp))

CollinErickson/GauPro documentation built on March 25, 2024, 11:20 p.m.