KernelComputer-class | R Documentation |
An S4 class to represent input for kernel matrix computations
## S4 method for signature 'KernelComputer'
show(object)
## S4 method for signature 'KernelComputer'
num_components(object)
## S4 method for signature 'KernelComputer'
num_evalpoints(object)
## S4 method for signature 'KernelComputer'
num_paramsets(object)
## S4 method for signature 'KernelComputer'
component_names(object)
object |
The object for which to call a class method. |
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.
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)
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