R: Augment data according to a tidied model

sw_augment {sweep} | R Documentation

## Augment data according to a tidied model

### Description

Given an R statistical model or other non-tidy object, add columns to the original dataset such as predictions, residuals and cluster assignments.

### Usage

    sw_augment(x, ...)

### Arguments

`x` | model or other R object to convert to data frame
`...` | other arguments passed to methods

### Details

`sw_augment()` is a wrapper for `broom::augment()`. The benefit of `sw_augment` is that it has methods for various time-series model classes such as `HoltWinters`, `ets`, `Arima`, etc.

For non-time series, `sw_augment()` defaults to `broom::augment()`. The only difference is that the return is a tibble.

Note that by convention the first argument is almost always `data`, which specifies the original data object. This is not part of the S3 signature, partly because it prevents rowwise_df_tidiers from taking a column name as the first argument.

### See Also

`broom::augment()`

[Package sweep version 0.2.3 Index]