R/aaa.R
, R/methods-KernelComputer.R
KernelComputer-class.Rd
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)
object | The object for which to call a class method. |
---|
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.
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)