# Prediction intervals from conformal methods

Source:`R/conformal_infer.R`

, `R/conformal_infer_cv.R`

, `R/conformal_infer_quantile.R`

, and 1 more
`predict.int_conformal_full.Rd`

Prediction intervals from conformal methods

## Usage

```
# S3 method for int_conformal_full
predict(object, new_data, level = 0.95, ...)
# S3 method for int_conformal_cv
predict(object, new_data, level = 0.95, ...)
# S3 method for int_conformal_quantile
predict(object, new_data, ...)
# S3 method for int_conformal_split
predict(object, new_data, level = 0.95, ...)
```

## Arguments

- object
An object produced by

`predict.int_conformal_full()`

.- new_data
A data frame of predictors.

- level
The confidence level for the intervals.

- ...
Not currently used.

## Value

A tibble with columns `.pred_lower`

and `.pred_upper`

. If
the computations for the prediction bound fail, a missing value is used. For
objects produced by `int_conformal_cv()`

, an additional `.pred`

column
is also returned (see Details below).

## Details

For the CV+. estimator produced by `int_conformal_cv()`

, the intervals
are centered around the mean of the predictions produced by the
resample-specific model. For example, with 10-fold cross-validation, `.pred`

is the average of the predictions from the 10 models produced by each fold.
This may differ from the prediction generated from a model fit that was
trained on the entire training set, especially if the training sets are
small.