GaussianPrediction-class {lgpr} | R Documentation |
An S4 class to represent analytically computed predictive distributions (conditional on hyperparameters) of an additive GP model
## S4 method for signature 'GaussianPrediction'
show(object)
## S4 method for signature 'GaussianPrediction'
component_names(object)
## S4 method for signature 'GaussianPrediction'
num_components(object)
## S4 method for signature 'GaussianPrediction'
num_paramsets(object)
## S4 method for signature 'GaussianPrediction'
num_evalpoints(object)
object |
GaussianPrediction object for which to apply a class method. |
show(GaussianPrediction)
: Print a summary about the object.
component_names(GaussianPrediction)
: Get names of components.
num_components(GaussianPrediction)
: Get number of components.
num_paramsets(GaussianPrediction)
: Get number of parameter combinations
(different parameter vectors) using which predictions were computed.
num_evalpoints(GaussianPrediction)
: Get number of points where
predictions were computed.
f_comp_mean
component means
f_comp_std
component standard deviations
f_mean
signal mean (on normalized scale)
f_std
signal standard deviation (on normalized scale)
y_mean
predictive mean (on original data scale)
y_std
predictive standard deviation (on original data scale)
x
a data frame of points (covariate values) where the function posteriors or predictive distributions have been evaluated