`R/aaa.R`

, `R/methods-Prediction.R`

`GaussianPrediction-class.Rd`

An S4 class to represent analytically computed predictive distributions (conditional on hyperparameters) of an additive GP model

```
# S4 method for GaussianPrediction
show(object)
# S4 method for GaussianPrediction
component_names(object)
# S4 method for GaussianPrediction
num_components(object)
# S4 method for GaussianPrediction
num_paramsets(object)
# S4 method for 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