If

`fit`

is for a model that marginalizes the latent signal`f`

(i.e.`is_f_sampled(fit)`

is`FALSE`

), this computes the analytic conditional posterior distributions of each model component, their sum, and the conditional predictive distribution. All these are computed for each (hyper)parameter draw (defined by`draws`

), or other parameter set (obtained by a reduction defined by`reduce`

). Results are stored in a GaussianPrediction object which is then returned.If

`fit`

is for a model that samples the latent signal`f`

(i.e.`is_f_sampled(fit)`

is`TRUE`

), this will extract these function samples, compute their sum, and a version of the sum`f`

that is transformed through the inverse link function. If`x`

is not`NULL`

, the function draws are extrapolated to the points specified by`x`

using kernel regression. Results are stored in a Prediction object which is then returned.

```
pred(
fit,
x = NULL,
reduce = function(x) base::mean(x),
draws = NULL,
verbose = TRUE,
STREAM = get_stream(),
c_hat_pred = NULL,
force = FALSE,
debug_kc = FALSE
)
```

- fit
An object of class lgpfit.

- x
A data frame of points where function posterior distributions and predictions should be computed or sampled. The function

`new_x`

provides an easy way to create it. If this is`NULL`

, the data points are used.- reduce
Reduction for parameters draws. Can be a function that is applied to reduce all parameter draws into one parameter set, or

`NULL`

(no reduction). Has no effect if`draws`

is specified.- draws
Indices of parameter draws to use, or

`NULL`

to use all draws.- verbose
Should more information and a possible progress bar be printed?

- STREAM
External pointer. By default obtained with

`rstan::get_stream()`

.- c_hat_pred
This is only used if the latent signal

`f`

was sampled. This input contains the values added to the sum`f`

before passing through inverse link function. Must be a vector with length equal to the number of prediction points. If original`c_hat`

was constant, then`c_hat_pred`

can be ignored, in which case this will by default use the same constant.- force
This is by default

`FALSE`

to prevent unintended large computations that might crash R or take forever. Set it to`TRUE`

try computing no matter what.- debug_kc
If this is

`TRUE`

, this only returns a KernelComputer object that is created internally. Meant for debugging.

An object of class GaussianPrediction or Prediction.

Other main functions:
`create_model()`

,
`draw_pred()`

,
`get_draws()`

,
`lgp()`

,
`prior_pred()`

,
`sample_model()`