An S4 class to represent input for kernel matrix computations

# S4 method for KernelComputer
show(object)

# S4 method for KernelComputer
num_components(object)

# S4 method for KernelComputer
num_evalpoints(object)

# S4 method for KernelComputer
num_paramsets(object)

# S4 method for KernelComputer
component_names(object)

## Arguments

object The object for which to call a class method.

## Methods (by generic)

• show: Print a summary about the object.

• num_components: Get number of components.

• num_evalpoints: Get number of evaluation points.

• num_paramsets: Get number of parameter sets.

• component_names: Get component names.

## Slots

input

Common input (for example parameter values).

K_input

Input for computing kernel matrices between data points (N x N). A list.

Ks_input

Input for computing kernel matrices between data and output points (P x N). A list.

Kss_input

Input for computing kernel matrices between output points (P x P). A list, empty if full_covariance=FALSE.

comp_names

Component names (character vector).

full_covariance

Boolean value determining if this can compute full predictive covariance matrices (or just marginal variance at each point).

no_separate_output_points

Boolean value determining if Ks_input and Kss_input are the same thing. Using this knowledge can reduce unnecessary computations of kernel matrices.

STREAM

external pointer (for calling 'Stan' functions)