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(KernelComputer): Print a summary about the object.
num_components(KernelComputer): Get number of components.
num_evalpoints(KernelComputer): Get number of evaluation points.
num_paramsets(KernelComputer): Get number of parameter sets.
component_names(KernelComputer): 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)